https://wiki.geneontology.org/api.php?action=feedcontributions&user=Slaulederkind&feedformat=atomGO Wiki - User contributions [en]2024-03-29T09:04:43ZUser contributionsMediaWiki 1.40.0https://wiki.geneontology.org/index.php?title=RGD_December_2017&diff=72331RGD December 20172018-12-11T16:45:54Z<p>Slaulederkind: /* 3. Methods and strategies for annotation */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2017 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Liz Bolton<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Jyothi Thota, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Manual Annotations 2016<br />
! Manual Annotations 2017<br />
! % Change<br />
|- <br />
| 19,548<br />
| 52,136<br />
| 53,502<br />
| +2.5%<br />
|-<br />
|}<br />
<br />
The number of genes with manual annotations has increased from 6,260 to 6,314(+74, +1.2%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2017, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: development-related disease genes, Huntington disease genes, and cancer genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# N/A<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# N/A<br />
<br />
c. Poster presentations with GO content<br />
<br />
# N/A<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed ~105 new terms/synonyms from December 2016 to December 2017. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2017&diff=66043RGD December 20172017-12-08T18:42:34Z<p>Slaulederkind: /* 5. Other Highlights */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2017 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Liz Bolton<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Jyothi Thota, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Manual Annotations 2016<br />
! Manual Annotations 2017<br />
! % Change<br />
|- <br />
| 19,548<br />
| 52,136<br />
| 53,502<br />
| +2.5%<br />
|-<br />
|}<br />
<br />
The number of genes with manual annotations has increased from 6,260 to 6,314(+74, +1.2%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2016, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: development-related disease genes, Huntington disease genes, and cancer genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# N/A<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# N/A<br />
<br />
c. Poster presentations with GO content<br />
<br />
# N/A<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed ~105 new terms/synonyms from December 2016 to December 2017. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2017&diff=66042RGD December 20172017-12-08T18:40:09Z<p>Slaulederkind: Created page with "== RGD, The Rat Genome Database, December 2017 == === 1. Staff working on GOC tasks === RGD Admin: Mary Shimoyama GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang,..."</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2017 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Liz Bolton<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Jyothi Thota, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Manual Annotations 2016<br />
! Manual Annotations 2017<br />
! % Change<br />
|- <br />
| 19,548<br />
| 52,136<br />
| 53,502<br />
| +2.5%<br />
|-<br />
|}<br />
<br />
The number of genes with manual annotations has increased from 6,260 to 6,314(+74, +1.2%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2016, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: development-related disease genes, Huntington disease genes, and cancer genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# N/A<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# N/A<br />
<br />
c. Poster presentations with GO content<br />
<br />
# N/A<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed ~105 new terms/synonyms from December 2016 to December 2017. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on YouTube, Vimeo.com, and rgd.mcw.edu.</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=2017_Corvallis_GOC_Meeting_Agenda&diff=638372017 Corvallis GOC Meeting Agenda2017-05-17T19:47:27Z<p>Slaulederkind: /* Attendees */</p>
<hr />
<div>=Day 1=<br />
<br />
== 9am Welcome, schedule and logistics ==<br />
* Remote attendees call in via Bluejeans: https://bluejeans.com/993661940<br />
* Schedule<br />
* Introductions<br />
<br />
<br />
==Overview/Plan for Upcoming Year==<br />
*GO PIs presentation<br />
*This year's goals<br />
<br />
==Pipeline Migration== <br />
Seth & Chris 20 mins<br />
<br />
== New APIs==<br />
<br />
Seth & Chris 20 mins<br />
<br />
== TermGenie replacement ==<br />
<br />
https://github.com/geneontology/go-ontology/issues/13472<br />
Chris 20 mins<br />
<br />
== Graph Store update ==<br />
Eric 10 mins<br />
<br />
==GO and Related Projects==<br />
<br />
===Licensing and GO===<br />
Seth 20 mins<br />
* Where we currently stand with licensing and possible issues<br />
* What others do with our data<br />
<br />
=== AGR ===<br />
<br />
*What does GO need to do for AGR?<br />
*Is there anything that GO curators should do any differently for this?<br />
*Parts of GO infrastructure being re-used by AGR (Chris)<br />
** db-xrefs.yaml<br />
*Data Formats (Chris)<br />
** BGI and GPI<br />
** Gene association JSON<br />
<br />
=== Planteome ===<br />
<br />
* How GO and Planteome contribute to one another Chris/Pankaj/Seth<br />
<br />
=== Other Projects ===<br />
<br />
*BioCaddie and db-xrefs.yaml (Chris)<br />
*Monarch (Chris)<br />
*Panther?<br />
*...<br />
<br />
==Identifiers==<br />
<br />
* Replacing double MGI (Chris)<br />
** https://github.com/geneontology/go-site/issues/346<br />
** https://github.com/geneontology/go-site/pull/338 AGR<br />
<br />
<br />
==Update on Ontology Editing==<br />
<br />
* David + Chris 20min<br />
* Design Pattern Updates: David OS + Chris 20 mins<br />
* Ontology Documentation: Moni 10 mins<br />
* [https://github.com/geneontology/go-ontology/issues/13384 Curator notes and propagation]<br />
* Proposal: text mining github tickets for ontology terms (Chris, Kimberly)<br />
<br />
==MF refactoring (Paul, DavidOS) ==<br />
<br />
30 mins<br />
<br />
* Issues: https://github.com/geneontology/molecular_function_refactoring/issues<br />
<br />
Emphasis on practical implications for LEGO curation (templates).<br />
<br />
== ECO ==<br />
<br />
Mapping to classic GO evidence codes. The official mapping of IMP to ECO is not sufficiently broad. Should cover non-genetic perturbations (e.g. pharmacological).<br />
<br />
IS THERE A TICKET FOR THIS ON THE ECO TRACKER?<br />
<br />
I think it might be this one:<br />
<br />
https://github.com/evidenceontology/evidenceontology/issues/117<br />
<br />
There are lots of things under the ECO code that maps to IDA that are perturbations, not assays e.g.: <br />
<br />
https://github.com/evidenceontology/evidenceontology/issues/123#issuecomment-281041854<br />
<br />
== Noctua and SIGNOR2 ==<br />
<br />
* https://github.com/geneontology/noctua/issues/413<br />
<br />
Chris/PaulT<br />
<br />
== GAFs and GPADs from Noctua models ==<br />
<br />
https://github.com/geneontology/noctua/issues/418<br />
<br />
David + others? 30 min<br />
<br />
*Where do we stand?<br />
*Challenges with complex models (evidence)<br />
*All of PRO IDS should be available in Noctua (ids for human, pombe, etc); can these be loaded from PRO directly (PRO to supply a GPI file).<br />
*GP-CC Should we allow direct GO part_of CC assertion (rather than via GO <-- enabled_by MF occurs_in --> CC). This is more accurate in some cases e.g. for membrane components.<br />
<br />
== Use of Qualifiers in Legacy Annotations ==<br />
<br />
(this should probably come before the go-cam->gaf pipeline above)<br />
<br />
* RO subset for use with GAF/GPAD in qualifier column (Chris/Kimberly/DavidOS)<br />
* [https://github.com/geneontology/go-annotation/issues/1517 New qualifiers for biological processes]<br />
* [https://github.com/geneontology/go-annotation/issues/1468 Incorporate expanded list of GP-GO term relations into annotation tools and files]<br />
* [https://github.com/geneontology/go-annotation/issues/1532 Regulation and causality]<br />
<br />
== The fate of simple processes==<br />
* What do we consider a single-step process and what is their future?<br />
* [https://github.com/geneontology/go-ontology/issues/12859 GH ticket about single step processes]<br />
* [https://github.com/geneontology/go-ontology/issues/13012 Is this a single step process?]<br />
<br />
==The distinction between cellular processes and processes, do we need it?==<br />
* [https://github.com/geneontology/go-ontology/issues/12849 GH ticket about cellular processes]<br />
** [https://docs.google.com/document/d/1QpfUY_LgeIryMj6EEAE05FXLE_894GalkerBU8dMuVU/edit# Additional document]<br />
* [https://gist.github.com/cmungall/4ed28123c3db832a7d99cbdd8e8a5920 Straw man BP refactor] Chris<br />
<br />
==Annotation of Viral Processes==<br />
*[https://github.com/geneontology/go-ontology/issues/13214 13214]<br />
*Taxon restriction?<br />
*Annotation of host proteins involved in, or co-opted for, viral reproduction<br />
**Transcription, translation of viral genome<br />
<br />
* DOS proposal for multi-organism annotation (reviving old proposal) - poss allowing non-cannonical function to be separable<br />
<br />
== Annotation QC issues ==<br />
=== HTP papers ===<br />
Helen, Pascale & Sylvain<br />
<br />
See notes /list of papers:<br />
<br />
=== Transcription-Factor decision tree (Breakout)===<br />
Ruth (20mins?)<br />
<br />
https://github.com/geneontology/go-annotation/issues/1463<br />
<br />
=== Modified protein binding ===<br />
Pascale & Sylvain<br />
<br />
https://github.com/geneontology/go-ontology/issues/12787<br />
<br />
=== GO Rules System ===<br />
Eric<br />
<br />
===Consistent use of the type field in GAFs/GPAD===<br />
<br />
Chris <br />
<br />
* E.g. https://github.com/geneontology/go-annotation/issues/1554<br />
<br />
== Enrichment Analysis ==<br />
Val & Seth<br />
* by default have the enrichment tool run directly on the GO annotation dataset <br />
* by default enable loading a background<br />
* currently missing a substantial number of annotations (e.g. fission yeast)<br />
* Via ontobio python library (Chris)<br />
** Example jupyter notebook: https://github.com/biolink/ontobio/blob/master/notebooks/Phenotype_Enrichment.ipynb<br />
<br />
== PAINT update==<br />
Pascale and Huaiyu<br />
<br />
* Analysis of the PAINT annotation.<br />
* Plan for production services/pipeline for PAINT annotations<br />
<br />
== Contacts for Curation Groups ==<br />
Pascale & David<br />
<br />
Some annotation groups are now gone (no longer annotating), therefore, can't dispute annotations and have no mechanism to update or change them, if needed. <br />
We need to have a mechanism for tracking the status better github go-annotation tracker for annotation disputes can we have some GOC superuser status in Protein2GO that allows GO curators to update annotations<br />
Some groups like JCVI, PAMGO no longer annotate - can GOC take control of these experimental annotations?<br />
<br />
== Community Relations ==<br />
<br />
= Attendees =<br />
<br />
Please add your name to the table if you intend to attend the meeting, the dinner, the Noctua workshop, and the Reactome workshop so we can get a headcount estimate. Thank you!<br />
{| {{Prettytable}} class='sortable'<br />
|-<br />
! Name<br />
! Organization<br />
! Are you planning to attend the GOC meeting<br />
! Are you planning to attend the GOC dinner<br />
! Are you bringing a poster? how many?<br />
! Are you planning to attend the Noctua workshop the day after the meeting, Sunday, June 4th?<br />
! Are you planning to attend the Reactome workshop on Monday, June 5th?<br />
|-<br />
| Giulia Antonazzo<br />
| FlyBase<br />
| Y<br />
| Y<br />
|<br />
| N<br />
| N<br />
|-<br />
| Helen Attrill<br />
| FlyBase<br />
| Y<br />
| Y<br />
|<br />
| N<br />
| N<br />
|-<br />
| Judy Blake<br />
| MGI<br />
| Y<br />
| Y<br />
| Y-1<br />
| N<br />
| N<br />
|-<br />
| Seth Carbon<br />
| Berkeley/LBL<br />
| Y<br />
| <br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Mike Cherry<br />
| SGD<br />
| Y<br />
| Y<br />
| N<br />
| N<br />
| N<br />
|-<br />
| Paul Thomas<br />
| USC<br />
| Y<br />
| Y<br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Laurel Cooper<br />
| Jaiswal Group/Oregon State<br />
| Y<br />
| <br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Stacia Engel<br />
| SGD<br />
| Y<br />
| N<br />
| N<br />
| N<br />
| N<br />
|-<br />
| Priyanka Garg<br />
| <br />
| Y<br />
| <br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Parul Gupta<br />
| Jaiswal Group/Oregon State<br />
| Y<br />
| <br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Tom Hayman<br />
| RGD<br />
| Y<br />
| Y<br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Emily Heald<br />
| SGD<br />
| Y<br />
| Y<br />
| N<br />
| Y<br />
| N<br />
|-<br />
| David Hill<br />
| MGI<br />
| Y<br />
| Y<br />
| N<br />
| Y<br />
| N<br />
|-<br />
| Doug Howe<br />
| ZFIN<br />
| Y<br />
| maybe<br />
| N<br />
| Y<br />
| N<br />
|-<br />
| Ceri Van Slyke<br />
| ZFIN<br />
| N<br />
| N<br />
| N<br />
| Y<br />
| N<br />
|-<br />
| Sridhar Ramachandran<br />
| ZFIN<br />
| N<br />
| N<br />
| N<br />
| Y<br />
| N<br />
|-<br />
| David Fashena<br />
| ZFIN<br />
| N<br />
| N<br />
| N<br />
| Y<br />
| N<br />
|-<br />
| Leyla Ruzica<br />
| ZFIN<br />
| N<br />
| N<br />
| N<br />
| Y<br />
| N<br />
|-<br />
| Pankaj Jaiswal<br />
| Reactome/Oregon State<br />
| Y<br />
| <br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Stan Laulederkind<br />
| RGD<br />
| Y<br />
| Y<br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Suzi Lewis<br />
| Berkeley/LBL<br />
| Y<br />
| <br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Ruth Lovering<br />
| UCL<br />
| Y<br />
| Y<br />
| Y-3<br />
| Y<br />
| Y<br />
|-<br />
| Austin Meier<br />
| Jaiswal Group/Oregon State<br />
| Y<br />
| <br />
|<br />
| Y<br />
| N<br />
|-<br />
| Moni Munoz-Torres<br />
| Berkeley/LBL<br />
| Y<br />
| Y<br />
|<br />
| Y<br />
| N<br />
|-<br />
| Sushma Naithani<br />
| Jaiswal Group/Oregon State<br />
| Y<br />
| <br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Darren Natale<br />
| PRO<br />
| Y<br />
| <br />
|<br />
| N<br />
| N<br />
|-<br />
| Sabrina Toro<br />
| Zfin<br />
| Y<br />
| maybe<br />
| N<br />
| Y<br />
| Y<br />
|-<br />
| Kimberly Van Auken<br />
| WB<br />
| Y<br />
| Y<br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Edith Wong<br />
| SGD<br />
| Y<br />
| Y<br />
| N<br />
| Y<br />
| N<br />
|-<br />
| Huaiyu Mi<br />
| USC<br />
| Y<br />
| <br />
|<br />
| Y<br />
| N<br />
|-<br />
| Chris Mungall<br />
| LBL<br />
| Y<br />
| Y<br />
|<br />
| Y<br />
| Y<br />
|-<br />
| Peter D'Eustachio<br />
| Reactome<br />
| Y<br />
| Y<br />
| N?<br />
| Y<br />
| Y<br />
|-<br />
| Maria Martin<br />
| EMBL-EBI<br />
| Y<br />
| Y<br />
| Y(1)<br />
| N<br />
| N<br />
|-<br />
| Tony Sawford<br />
| EMBL-EBI<br />
| Y<br />
| Y<br />
| N<br />
| N<br />
| N<br />
|-<br />
| Alice Shypitsyna<br />
| EMBL-EBI<br />
| Y<br />
| Y<br />
| Y(1)<br />
| Y<br />
| ?<br />
|-<br />
| George Georghiou<br />
| EMBL-EBI<br />
| Y<br />
| Y<br />
| Y(1)<br />
| Y<br />
| Y<br />
|-<br />
| Pascale Gaudet<br />
| GOC/SIB Swiss Institute of Bioinformtaics<br />
| Y<br />
| Y<br />
| ?<br />
| Y<br />
| Y<br />
|-<br />
|-<br />
| David OS<br />
| EBI<br />
| Y<br />
| Y<br />
| N<br />
| AM<br />
| N<br />
|-<br />
| Malcolm Fisher<br />
| Xenbase<br />
| Y<br />
| Y<br />
| N<br />
| Y<br />
| Y<br />
|-<br />
|}<br />
<br />
*NOT ATTENDING:<br />
<br />
[[Category: GO Consortium Meetings]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=2017_Corvallis_GOC_Meeting_Agenda&diff=636482017 Corvallis GOC Meeting Agenda2017-04-25T16:04:54Z<p>Slaulederkind: /* Attendees */</p>
<hr />
<div>=Day 1=<br />
<br />
== 9am Welcome, schedule and logistics ==<br />
* Remote attendees call in via Bluejeans: https://bluejeans.com/993661940<br />
* Schedule<br />
* Introductions<br />
<br />
<br />
==Overview/Plan for Upcoming Year==<br />
*GO PIs presentation<br />
*This year's goals<br />
<br />
==Pipeline Migration== <br />
Seth & Chris 20 mins<br />
<br />
== New APIs==<br />
<br />
Seth & Chris 20 mins<br />
<br />
== TermGenie replacement ==<br />
<br />
Chris 20 mins<br />
<br />
== Graph Store update ==<br />
Eric 10 mins<br />
<br />
==GO and AGR==<br />
*What does GO need to do for AGR?<br />
*Is there anything that GO curators should do any differently for this? <br />
<br />
==Introduction to Ontology Editing (David, Chris)==<br />
*How are new terms added?<br />
<br />
==MF refactoring (Paul, David) ==<br />
<br />
<br />
== ECO ==<br />
<br />
Mapping to classic GO evidence codes. The official mapping of IMP to ECO is not sufficiently broad. Should cover non-genetic perturbations (e.g. pharmacological).<br />
<br />
== GAFs and GPADs from Noctua models ==<br />
*Where do we stand?<br />
*Challenges with complex models (evidence)<br />
*All of PRO IDS should be available in Noctua (ids for human, pombe, etc); can these be loaded from PRO directly?<br />
<br />
== The fate of simple processes==<br />
* What do we consider a single-step process and what is their future?<br />
* [https://github.com/geneontology/go-ontology/issues/12859 GH ticket about single step processes]<br />
* [https://github.com/geneontology/go-ontology/issues/13012 Is this a single step process?]<br />
<br />
==The distinction between cellular processes and processes, do we need it?==<br />
* [https://github.com/geneontology/go-ontology/issues/12849 GH ticket about cellular processes]<br />
<br />
<br />
== Annotation QC issues ==<br />
=== HTP papers ===<br />
Pascale & Sylvain<br />
See notes /list of papers: <br />
<br />
<br />
=== Modified protein binding ===<br />
Pascale & Sylvain<br />
https://github.com/geneontology/go-ontology/issues/12787<br />
<br />
== Enrichment Analysis ==<br />
Val & Seth<br />
* by default have the enrichment tool run directly on the GO annotation dataset <br />
* by default enable loading a background<br />
* currently missing a substantial number of annotations (e.g. fission yeast)<br />
<br />
<br />
<br />
== Contacts for Curation Groups ==<br />
Pascale & David<br />
Some annotation groups are now gone (no longer annotating), therefore, can't dispute annotations and have no mechanism to update or change them, if needed. <br />
We need to have a mechanism for tracking the status better github go-annotation tracker for annotation disputes can we have some GOC superuser status in Protein2GO that allows GO curators to update annotations<br />
Some groups like JCVI, PAMGO no longer annotate - can GOC take control of these experimental annotations? <br />
<br />
= Attendees =<br />
<br />
Please add your name to the table if you intend to attend the meeting, the dinner, the Noctua workshop, and the Reactome workshop so we can get a headcount estimate. Thank you!<br />
{| {{Prettytable}} class='sortable'<br />
|-<br />
! Name<br />
! Organization<br />
! Are you planning to attend the GOC meeting<br />
! Are you planning to attend the GOC dinner<br />
! Are you planning to attend the Noctua workshop the day after the meeting, Sunday, June 4th?<br />
! Are you planning to attend the Reactome workshop on Monday, June 5th?<br />
|-<br />
| Giulia Antonazzo<br />
| FlyBase<br />
| Y<br />
| Y<br />
| N<br />
| N<br />
|-<br />
| Helen Attrill<br />
| FlyBase<br />
| Y<br />
| <br />
| N<br />
| N<br />
|-<br />
| Judy Blake<br />
| MGI<br />
| Y<br />
| <br />
| ?<br />
| ?<br />
|-<br />
| Seth Carbon<br />
| Berkeley/LBL<br />
| Y<br />
| <br />
| Y<br />
| Y<br />
|-<br />
| Mike Cherry<br />
| SGD<br />
| Y<br />
| <br />
| N<br />
| N<br />
|-<br />
| Paul Thomas<br />
| USC<br />
| Y<br />
| Y<br />
| Y<br />
| Y<br />
|-<br />
| Laurel Cooper<br />
| Jaiswal Group/Oregon State<br />
| Y<br />
| <br />
| Y<br />
| Y<br />
|-<br />
| Stacia Engel<br />
| SGD<br />
| Y<br />
| <br />
| N<br />
| N<br />
|-<br />
| Priyanka Garg<br />
| <br />
| Y<br />
| <br />
| Y<br />
| Y<br />
|-<br />
| Parul Gupta<br />
| Jaiswal Group/Oregon State<br />
| Y<br />
| <br />
| Y<br />
| Y<br />
|-<br />
| Tom Hayman<br />
| RGD<br />
| Y<br />
| <br />
| Y<br />
| Y<br />
|-<br />
| Emily Heald<br />
| SGD<br />
| Y<br />
| <br />
| Y<br />
| N<br />
|-<br />
| David Hill<br />
| MGI<br />
| Y<br />
| <br />
| Y<br />
| N<br />
|-<br />
| Doug Howe<br />
| Zfin<br />
| Y<br />
| <br />
| Y<br />
| N<br />
|-<br />
| Pankaj Jaiswal<br />
| Reactome/Oregon State<br />
| Y<br />
| <br />
| Y<br />
| Y<br />
|-<br />
| Stan Laulederkind<br />
| RGD<br />
| Y<br />
| Y<br />
| Y<br />
| N<br />
|-<br />
| Suzi Lewis<br />
| Berkeley/LBL<br />
| Y<br />
| <br />
| Y<br />
| Y<br />
|-<br />
| Ruth Lovering<br />
| UCL<br />
| Y<br />
| <br />
| Y<br />
| Y<br />
|-<br />
| Austin Meier<br />
| Jaiswal Group/Oregon State<br />
| Y<br />
| <br />
| Y<br />
| N<br />
|-<br />
| Moni Munoz-Torres<br />
| Berkeley/LBL<br />
| Y<br />
| <br />
| Y<br />
| N<br />
|-<br />
| Sushma Naithani<br />
| Jaiswal Group/Oregon State<br />
| Y<br />
| <br />
| Y<br />
| Y<br />
|-<br />
| Darren Natale<br />
| PRO<br />
| Y<br />
| <br />
| N<br />
| N<br />
|-<br />
| Sabrina Toro<br />
| Zfin<br />
| Y<br />
| <br />
| Y<br />
| Y<br />
|-<br />
| Kimberly Van Auken<br />
| WB<br />
| Y<br />
| Y<br />
| Y<br />
| Y<br />
|-<br />
| Edith Wong<br />
| SGD<br />
| Y<br />
| <br />
| Y<br />
| N<br />
|-<br />
| Huaiyu Mi<br />
| USC<br />
| Y<br />
| <br />
| Y<br />
| N<br />
|-<br />
| Chris Mungall<br />
| LBL<br />
| Y<br />
| Y<br />
| Y<br />
| Y<br />
|-<br />
| Peter D'Eustachio<br />
| Reactome<br />
| Y<br />
| Y<br />
| Y<br />
| Y<br />
|-<br />
|}<br />
<br />
*NOT ATTENDING:<br />
<br />
[[Category: GO Consortium Meetings]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2016&diff=62735RGD December 20162016-12-14T22:43:16Z<p>Slaulederkind: /* RGD, The Rat Genome Database, December 2016 */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2016 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Omid Ghiasvand, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2015<br />
! Annotations 2016<br />
! % Change<br />
|- <br />
| 39,206<br />
| 547,064 (314,567 non-IEA)<br />
| 599,250 (323,853 non-IEA)<br />
| +9.5%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2015 to December 2016. The number of manual annotations from RGD has increased from 49,791 to 52,136 (+ 2,345 annotations, +4.7%) and the number of genes with manual annotations has increased from 5,998 to 6,260 (+262, +4.4%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2016, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: hematologic disease genes and development-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Shimoyama M, Laulederkind SJ, De Pons J, Nigam R, Smith JR, Tutaj M, Petri V, Hayman GT, Wang SJ, Ghiasvand O, Thota J, Dwinell MR. Exploring human disease using the Rat Genome Database. Dis Model Mech. 2016 Oct 1;9(10):1089-1095.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# N/A<br />
<br />
c. Poster presentations with GO content<br />
<br />
# N/A<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 150 - 160 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2015 to December 2016. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on YouTube, Vimeo.com, and rgd.mcw.edu.<br />
<br />
* OLGA (Object List Generator tool) Tutorial- including information on using curated GO data<br />
* Gene Annotator Tutorial- including information on using curated GO data</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2016&diff=62734RGD December 20162016-12-14T22:42:44Z<p>Slaulederkind: /* RGD, The Rat Genome Database, December 2016 */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2016 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Omid Ghiasvand, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2015<br />
! Annotations 2016<br />
! % Change<br />
|- <br />
| 39,206<br />
| 547,064 (314,567 non-IEA)<br />
| 599,250 (323,853 non-IEA)<br />
| +9.5%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2015 to December 2016. The number of manual annotations from RGD has increased from 49,791 to 52,136 (+ 2,345 annotations, +4.7%) and the number of genes with manual annotations has increased from 5,998 to 6,260 (+262, +4.4%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2016, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: hematologic disease genes and development-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Shimoyama M, Laulederkind SJ, De Pons J, Nigam R, Smith JR, Tutaj M, Petri V, Hayman GT, Wang SJ, Ghiasvand O, Thota J, Dwinell MR. Exploring human disease using the Rat Genome Database. Dis Model Mech. 2016 Oct 1;9(10):1089-1095.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# N/A<br />
<br />
c. Poster presentations with GO content<br />
<br />
# N/A<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 150 - 160 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2014 to December 2015. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on YouTube, Vimeo.com, and rgd.mcw.edu.<br />
<br />
* OLGA (Object List Generator tool) Tutorial- including information on using curated GO data<br />
* Gene Annotator Tutorial- including information on using curated GO data</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2016&diff=62733RGD December 20162016-12-14T22:40:04Z<p>Slaulederkind: /* RGD, The Rat Genome Database, December 2016 */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2016 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Omid Ghiasvand, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 39,206<br />
| 547,064 (314,567 non-IEA)<br />
| 599,250 (323,853 non-IEA)<br />
| +9.5%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2015 to December 2016. The number of manual annotations from RGD has increased from 49,791 to 52,136 (+ 2,345 annotations, +4.7%) and the number of genes with manual annotations has increased from 5,998 to 6,260 (+262, +4.4%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2016, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: hematologic disease genes and development-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Shimoyama M, Laulederkind SJ, De Pons J, Nigam R, Smith JR, Tutaj M, Petri V, Hayman GT, Wang SJ, Ghiasvand O, Thota J, Dwinell MR. Exploring human disease using the Rat Genome Database. Dis Model Mech. 2016 Oct 1;9(10):1089-1095.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# N/A<br />
<br />
c. Poster presentations with GO content<br />
<br />
# N/A<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 150 - 160 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2014 to December 2015. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on YouTube, Vimeo.com, and rgd.mcw.edu.<br />
<br />
* OLGA (Object List Generator tool) Tutorial- including information on using curated GO data<br />
* Gene Annotator Tutorial- including information on using curated GO data</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2016&diff=62732RGD December 20162016-12-14T22:38:00Z<p>Slaulederkind: /* RGD, The Rat Genome Database, December 2016 */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2016 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Omid Ghiasvand, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 39,206<br />
| 547,064 (314,567 non-IEA)<br />
| 599,250 (323,853 non-IEA)<br />
| +9.5%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2015 to December 2016. The number of manual annotations from RGD has increased from 49,791 to 52,136 (+ 2,345 annotations, +4.7%) and the number of genes with manual annotations has increased from 5,998 to 6,260 (+262, +4.4%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2016, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: hematologic disease genes and development-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Liu W, Laulederkind SJ, Hayman GT, Wang SJ, Nigam R, Smith JR, De Pons J, Dwinell MR, Shimoyama M. OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database (Oxford). 2015 Jan 25;2015. pii: bau129. doi: 10.1093/database/bau129. Print 2015.<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2015 Jan;43(Database issue):D743-50. doi: 10.1093/nar/gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind - lightning talk based on poster mentioned below, included information on curating GO data <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind, Weisong Liu, Marek Tutaj, G. Thomas Hayman, Rajni Nigam, Victoria Petri, J. R. Smith, Shur-Jen Wang, Jeff De Pons, M. R. Dwinell, Mary Shimoyama - included information on curating GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 400 - 450 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2014 to December 2015. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on YouTube, Vimeo.com, and rgd.mcw.edu.<br />
<br />
* OLGA (Object List Generator tool) Tutorial- including information on using curated GO data<br />
* Gene Annotator Tutorial- including information on using curated GO data</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2016&diff=62731RGD December 20162016-12-14T22:32:40Z<p>Slaulederkind: /* RGD, The Rat Genome Database, December 2016 */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2016 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Omid Ghiasvand, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 39,206<br />
| 547,064 (314,567 non-IEA)<br />
| 599,250 (323,853 non-IEA)<br />
| +9.5%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2015 to December 2016. The number of manual annotations from RGD has increased from 44,967 to 49,791 (+ 4,824 annotations, +11%) and the number of genes with manual annotations has increased from 5,625 to 5,998 (+373, +7%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2016, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: hematologic disease genes and development-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Liu W, Laulederkind SJ, Hayman GT, Wang SJ, Nigam R, Smith JR, De Pons J, Dwinell MR, Shimoyama M. OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database (Oxford). 2015 Jan 25;2015. pii: bau129. doi: 10.1093/database/bau129. Print 2015.<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2015 Jan;43(Database issue):D743-50. doi: 10.1093/nar/gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind - lightning talk based on poster mentioned below, included information on curating GO data <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind, Weisong Liu, Marek Tutaj, G. Thomas Hayman, Rajni Nigam, Victoria Petri, J. R. Smith, Shur-Jen Wang, Jeff De Pons, M. R. Dwinell, Mary Shimoyama - included information on curating GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 400 - 450 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2014 to December 2015. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on YouTube, Vimeo.com, and rgd.mcw.edu.<br />
<br />
* OLGA (Object List Generator tool) Tutorial- including information on using curated GO data<br />
* Gene Annotator Tutorial- including information on using curated GO data</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2016&diff=62729RGD December 20162016-12-14T21:10:00Z<p>Slaulederkind: Created page with "== RGD, The Rat Genome Database, December 2016 == === 1. Staff working on GOC tasks === RGD Admin: Mary Shimoyama GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang,..."</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2016 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Omid Ghiasvand, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 39,206<br />
| 547,064 (314,567 non-IEA)<br />
| 599,250 (323,853 non-IEA)<br />
| +9.5%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2015 to December 2016. The number of manual annotations from RGD has increased from 44,967 to 49,791 (+ 4,824 annotations, +11%) and the number of genes with manual annotations has increased from 5,625 to 5,998 (+373, +7%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2015, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: sensory organ disease genes and age-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Liu W, Laulederkind SJ, Hayman GT, Wang SJ, Nigam R, Smith JR, De Pons J, Dwinell MR, Shimoyama M. OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database (Oxford). 2015 Jan 25;2015. pii: bau129. doi: 10.1093/database/bau129. Print 2015.<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2015 Jan;43(Database issue):D743-50. doi: 10.1093/nar/gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind - lightning talk based on poster mentioned below, included information on curating GO data <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind, Weisong Liu, Marek Tutaj, G. Thomas Hayman, Rajni Nigam, Victoria Petri, J. R. Smith, Shur-Jen Wang, Jeff De Pons, M. R. Dwinell, Mary Shimoyama - included information on curating GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 400 - 450 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2014 to December 2015. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on YouTube, Vimeo.com, and rgd.mcw.edu.<br />
<br />
* OLGA (Object List Generator tool) Tutorial- including information on using curated GO data<br />
* Gene Annotator Tutorial- including information on using curated GO data</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62259Annotation Conf. Call 2016-10-252016-10-24T20:44:14Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
'''Discussion Points'''<br />
<br /><br />
# What can be done with ferritin annotations, since a specific subunit was non identified in the paper? <br />
# Should colocalization (IEP) data be used for biological process annotations?<br />
# If an iron transport annotation is made, does an iron homeostasis annotation impart any additional information?<br />
# Is "intestinal absorption" too broad? Should an intestinal iron absorption term be requested?<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene Symbol, Gene Name<br />
! GO term/ID<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
!''Biological Process''<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| Which ferritin subunit?<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
| Tf, transferrin<br />
| ferric iron transport GO:0015682<br />
| IDA<br />
| RGD<br />
|<br />
| <br />
|-<br />
| ferritin<br />
| ferric ion import GO:0033216<br />
| ?<br />
| SGD<br />
|occurs_in UBERON:0000320 duodenal mucosa<br />
| <br />
|- <br />
| Tf, transferrin<br />
| ferric ion import GO:0033216<br />
| ?<br />
| SGD<br />
|occurs_in UBERON:0000320 duodenal mucosa<br />
| <br />
|-<br />
| Tf, transferrin<br />
| GO:0098706 -ferric iron import across plasma membrane <br />
| IEP<br />
| WB<br />
|<br />
| <br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0098706 -ferric iron import across plasma membrane <br />
| IEP<br />
| WB<br />
|<br />
|<br />
|-<br />
| ferritin<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| Which ferritin subunit?<br />
|- <br />
| Tf, transferrin<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| <br />
|-<br />
| ferritin, Fth1, Ftl1<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0000320) duodenal mucosa|occurs_in(UBERON:0016512) lumen of duodenum<br />
| <br />
|- <br />
| Tf, transferrin<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0016512)lumen of duodenum<br />
| <br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
|<br />
|- <br />
| Tf, transferrin<br />
| GO:0050892 - intestinal absorption<br />
| IEP<br />
| WB<br />
| has_input(ChEBI:29034)<br />
| Maybe request "intestinal iron ion absorption".<br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0050892 - intestinal absorption<br />
| IEP<br />
| WB<br />
| has_input(ChEBI:29034)<br />
|<br />
|- <br />
| Tf, transferrin<br />
| response to iron ion GO:0010039<br />
| IEP<br />
| RGD<br />
| <br />
| movement between compartments dependent on iron level in diet<br />
|-<br />
| Tfrc, transferrin receptor<br />
| response to iron ion GO:0010039<br />
| IEP<br />
| RGD<br />
|<br />
|<br />
|- <br />
| human ferritin, FTH1 (UniProtKB:P02794), FTL (UniProtKB:P02792)<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
|- <br />
| human TF (UniProtKB:P02787)<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
|- <br />
| human TFRC (UniProtKB:P02786)<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
|-<br />
!''Cellular Component''<br />
|- <br />
| Tf, transferrin<br />
| cell tip GO:0051286<br />
| IDA<br />
| RGD<br />
| <br />
| Figure 5 - ID, 15 min; text description<br />
|-<br />
| Tfrc, transferrin receptor<br />
| cell surface GO:0009986<br />
| IDA<br />
| RGD<br />
|<br />
| Figure 5; text description<br />
|- <br />
| Tfrc, transferrin receptor<br />
| GO:0031528 - microvillus membrane<br />
| IDA<br />
| WB<br />
| <br />
| <br />
|-<br />
| Tf, transferrin, Fth1, Ftl1, ferritin <br />
| GO:0005615 - extracellular space<br />
| IDA<br />
| WB<br />
| <br />
| <br />
|-<br />
!''Molecular Function''<br />
|-<br />
| Fth1, Ftl1, ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
| FB, Tair, WB<br />
| occurs_in UBERON:0000320 duodenal mucosa<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
| FB, Tair, WB<br />
| occurs_in UBERON:0000320 duodenal mucosa<br />
|<br />
|-<br />
| Tf, transferrin<br />
| ferric iron binding GO:0008199<br />
| IDA<br />
| RGD, SGD<br />
| <br />
|<br />
|-<br />
| ferritin<br />
| ferric iron binding GO:0008199<br />
| IDA<br />
| SGD<br />
| <br />
|<br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0004998 - transferrin receptor activity<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0008346) duodenal epithelium<br />
| IEP for MF annotation???<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62258Annotation Conf. Call 2016-10-252016-10-24T20:31:13Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
'''Discussion Points'''<br />
<br /><br />
# What can be done with ferritin annotations, since a specific subunit was non identified in the paper? <br />
# Should colocalization (IEP) data be used for biological process annotations?<br />
# If an iron transport annotation is made, does an iron homeostasis annotation impart any additional information?<br />
# Is "intestinal absorption" too broad? Should an intestinal iron absorption term be requested?<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
!''Biological Process''<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| Which ferritin subunit?<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
| Tf, transferrin<br />
| ferric iron transport GO:0015682<br />
| IDA<br />
| RGD<br />
|<br />
| <br />
|-<br />
| ferritin<br />
| ferric ion import GO:0033216<br />
| ?<br />
| SGD<br />
|occurs_in UBERON:0000320 duodenal mucosa<br />
| <br />
|- <br />
| Tf, transferrin<br />
| ferric ion import GO:0033216<br />
| ?<br />
| SGD<br />
|occurs_in UBERON:0000320 duodenal mucosa<br />
| <br />
|-<br />
| Tf, transferrin<br />
| GO:0098706 -ferric iron import across plasma membrane <br />
| IEP<br />
| WB<br />
|<br />
| <br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0098706 -ferric iron import across plasma membrane <br />
| IEP<br />
| WB<br />
|<br />
|<br />
|-<br />
| ferritin<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| Which ferritin subunit?<br />
|- <br />
| Tf, transferrin<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| <br />
|-<br />
| ferritin, Fth1, Ftl1<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0000320) duodenal mucosa|occurs_in(UBERON:0016512) lumen of duodenum<br />
| <br />
|- <br />
| Tf, transferrin<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0016512)lumen of duodenum<br />
| <br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
|<br />
|- <br />
| Tf, transferrin<br />
| GO:0050892 - intestinal absorption<br />
| IEP<br />
| WB<br />
| has_input(ChEBI:29034)<br />
| Maybe request "intestinal iron ion absorption".<br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0050892 - intestinal absorption<br />
| IEP<br />
| WB<br />
| has_input(ChEBI:29034)<br />
|<br />
|- <br />
| Tf, transferrin<br />
| response to iron ion GO:0010039<br />
| IEP<br />
| RGD<br />
| <br />
| movement between compartments dependent on iron level in diet<br />
|-<br />
| Tfrc, transferrin receptor<br />
| response to iron ion GO:0010039<br />
| IEP<br />
| RGD<br />
|<br />
|<br />
|- <br />
| human ferritin, FTH1 (UniProtKB:P02794), FTL (UniProtKB:P02792)<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
|- <br />
| human TF (UniProtKB:P02787)<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
|- <br />
| human TFRC (UniProtKB:P02786)<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
|-<br />
!''Cellular Component''<br />
|- <br />
| Tf, transferrin<br />
| cell tip GO:0051286<br />
| IDA<br />
| RGD<br />
| <br />
| Figure 5 - ID, 15 min; text description<br />
|-<br />
| Tfrc, transferrin receptor<br />
| cell surface GO:0009986<br />
| IDA<br />
| RGD<br />
|<br />
| Figure 5; text description<br />
|- <br />
| Tfrc, transferrin receptor<br />
| GO:0031528 - microvillus membrane<br />
| IDA<br />
| WB<br />
| <br />
| <br />
|-<br />
| Tf, transferrin, Fth1, Ftl1, ferritin <br />
| GO:0005615 - extracellular space<br />
| IDA<br />
| WB<br />
| <br />
| <br />
|-<br />
!''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62257Annotation Conf. Call 2016-10-252016-10-24T20:13:51Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
'''Discussion Points'''<br />
<br /><br />
# What can be done with ferritin annotations, since a specific subunit was non identified in the paper? <br />
# Should colocalization (IEP) data be used for biological process annotations?<br />
# If an iron transport annotation is made, does an iron homeostasis annotation impart any additional information?<br />
# Is "intestinal absorption" too broad? Should an intestinal iron absorption term be requested?<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
!''Biological Process''<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| Which ferritin subunit?<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
| Tf, transferrin<br />
| ferric iron transport GO:0015682<br />
| IDA<br />
| RGD<br />
|<br />
| <br />
|-<br />
| ferritin<br />
| ferric ion import GO:0033216<br />
| ?<br />
| SGD<br />
|occurs_in UBERON:0000320 duodenal mucosa<br />
| <br />
|- <br />
| Tf, transferrin<br />
| ferric ion import GO:0033216<br />
| ?<br />
| SGD<br />
|occurs_in UBERON:0000320 duodenal mucosa<br />
| <br />
|-<br />
| Tf, transferrin<br />
| GO:0098706 -ferric iron import across plasma membrane <br />
| IEP<br />
| WB<br />
|<br />
| <br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0098706 -ferric iron import across plasma membrane <br />
| IEP<br />
| WB<br />
|<br />
|<br />
|-<br />
| ferritin<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| Which ferritin subunit?<br />
|- <br />
| Tf, transferrin<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| <br />
|-<br />
| ferritin, Fth1, Ftl1<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0000320) duodenal mucosa|occurs_in(UBERON:0016512) lumen of duodenum<br />
| <br />
|- <br />
| Tf, transferrin<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0016512)lumen of duodenum<br />
| <br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
|<br />
|- <br />
| Tf, transferrin<br />
| GO:0050892 - intestinal absorption<br />
| IEP<br />
| WB<br />
| has_input(ChEBI:29034)<br />
| Maybe request "intestinal iron ion absorption".<br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0050892 - intestinal absorption<br />
| IEP<br />
| WB<br />
| has_input(ChEBI:29034)<br />
|<br />
|- <br />
| Tf, transferrin<br />
| response to iron ion GO:0010039<br />
| IEP<br />
| RGD<br />
| <br />
| movement between compartments dependent on iron level in diet<br />
|-<br />
| Tfrc, transferrin receptor<br />
| response to iron ion GO:0010039<br />
| IEP<br />
| RGD<br />
|<br />
|<br />
|- <br />
| human ferritin, FTH1 (UniProtKB:P02794), FTL (UniProtKB:P02792)<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
|- <br />
| Tf, transferrin<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
|-<br />
!''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
!''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62256Annotation Conf. Call 2016-10-252016-10-24T20:03:16Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
'''Discussion Points'''<br />
<br /><br />
# What can be done with ferritin annotations, since a specific subunit was non identified in the paper? <br />
# Should colocalization (IEP) data be used for biological process annotations?<br />
# If an iron transport annotation is made, does an iron homeostasis annotation impart any additional information?<br />
# Is "intestinal absorption" too broad? Should an intestinal iron absorption term be requested?<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
!''Biological Process''<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| Which ferritin subunit?<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
| Tf, transferrin<br />
| ferric iron transport GO:0015682<br />
| IDA<br />
| RGD<br />
|<br />
| <br />
|-<br />
| ferritin<br />
| ferric ion import GO:0033216<br />
| ?<br />
| SGD<br />
|occurs_in UBERON:0000320 duodenal mucosa<br />
| <br />
|- <br />
| Tf, transferrin<br />
| ferric ion import GO:0033216<br />
| ?<br />
| SGD<br />
|occurs_in UBERON:0000320 duodenal mucosa<br />
| <br />
|-<br />
| Tf, transferrin<br />
| GO:0098706 -ferric iron import across plasma membrane <br />
| IEP<br />
| WB<br />
|<br />
| <br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0098706 -ferric iron import across plasma membrane <br />
| IEP<br />
| WB<br />
|<br />
|<br />
|-<br />
| ferritin<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| Which ferritin subunit?<br />
|- <br />
| Tf, transferrin<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion homeostasis GO:0055072<br />
| IDA<br />
| FB<br />
|<br />
| <br />
|-<br />
| ferritin, Fth1, Ftl1<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
|- <br />
| Tf, transferrin<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
|-<br />
| Tfrc, transferrin receptor<br />
| GO:0060586 - multicellular organismal iron ion homeostasis<br />
| IEP<br />
| WB<br />
| occurs_in(UBERON:0002114) duodenum<br />
| <br />
!''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
!''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62255Annotation Conf. Call 2016-10-252016-10-24T19:42:33Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
'''Discussion Points'''<br />
<br /><br />
# What can be done with ferritin annotations, since a specific subunit was non identified in the paper? <br />
# Should colocalization (IEP) data be used for biological process annotations?<br />
# If an iron transport annotation is made, does an iron homeostasis annotation impart any additional information?<br />
# Is "intestinal absorption" too broad? Should an intestinal iron absorption term be requested?<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
!''Biological Process''<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| Which ferritin subunit?<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
| FB, Tair<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
| Tf, transferrin<br />
| ferric iron transport GO:0015682<br />
| IDA<br />
| RGD<br />
|<br />
| <br />
|-<br />
| ferritin<br />
| ferric ion import GO:0033216<br />
| ?<br />
| SGD<br />
|occurs_in UBERON:0000320 duodenal mucosa<br />
| Which ferritin subunit?<br />
|- <br />
| Tf, transferrin<br />
| ferric ion import GO:0033216<br />
| ?<br />
| SGD<br />
|occurs_in UBERON:0000320 duodenal mucosa<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
!''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
!''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62254Annotation Conf. Call 2016-10-252016-10-24T19:34:31Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
'''Discussion Points'''<br />
<br /><br />
# What can be done with ferritin annotations, since a specific subunit was non identified in the paper? <br />
# Should colocalization (IEP) data be used for biological process annotations?<br />
# If an iron transport annotation is made, does an iron homeostasis annotation impart any additional information?<br />
# Is "intestinal absorption" too broad? Should an intestinal iron absorption term be requested?<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
!''Biological Process''<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
!''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
!''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62253Annotation Conf. Call 2016-10-252016-10-24T19:33:05Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
'''Discussion Points'''<br />
<br /><br />
# What can be done with ferritin annotations, since a specific subunit was non identified in the paper? <br />
# Should colocalization (IEP) data be used for biological process annotations?<br />
# If an iron transport annotation is made, does an iron homeostasis annotation impart any additional information?<br />
# Is "intestinal absorption" too broad? Should an intestinal iron absorption term be requested?<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62251Annotation Conf. Call 2016-10-252016-10-24T18:36:56Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
'''Discussion Points'''<br />
<br /><br />
# What can be done with ferritin annotations, since a specific subunit was non identified in the paper? <br />
# Should colocalization (IEP) data be used for biological process annotations?<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62250Annotation Conf. Call 2016-10-252016-10-24T17:49:54Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
'''Discussion Points'''<br />
<br /><br />
# What can be done with ferritin annotations, since ferritin is a heteromultimer and a specific subunit was non identified in the paper? <br />
# <br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62249Annotation Conf. Call 2016-10-252016-10-24T17:49:01Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
'''Discussion Points'''<br />
<br /><br />
# What can be done with ferritin annotations, since ferritin is a heteromultimer? <br />
# <br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62248Annotation Conf. Call 2016-10-252016-10-24T17:46:33Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
'''Discussion Points'''<br />
<br /><br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62247Annotation Conf. Call 2016-10-252016-10-24T17:34:11Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! Annotation Source<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62246Annotation Conf. Call 2016-10-252016-10-24T17:33:15Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! With/From<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62245Annotation Conf. Call 2016-10-252016-10-24T17:31:53Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! GO ID/term<br />
! Evidence Code<br />
! With/From<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| Tf, transferrin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| ferritin<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tfrc, transferrin receptor<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Tfrc or Tfr2?<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Molecular Function''<br />
|-<br />
| ferritin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62199Annotation Conf. Call 2016-10-252016-10-19T21:36:38Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! Qualifier<br />
! GO ID/term<br />
! Evidence Code<br />
! With/From<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| Tf, transferrin<br />
|<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| ferritin<br />
|<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tfrc, transferrin receptor<br />
|<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
|<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Molecular Function''<br />
|-<br />
| ferritin<br />
|<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tf, transferrin<br />
|<br />
| iron ion binding, GO:0005506<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62198Annotation Conf. Call 2016-10-252016-10-19T21:32:43Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! Qualifier<br />
! GO ID/term<br />
! Evidence Code<br />
! With/From<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| Tf, transferrin<br />
|<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| transport is inferred from radioactive Fe sequential colocalizing with location of each of the proteins in different parts of the duodenum<br />
|-<br />
| ferritin<br />
|<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Which ferritin subunit?<br />
|-<br />
| Tfrc, transferrin receptor<br />
|<br />
| iron ion transport GO:0006826<br />
| IDA<br />
|<br />
|<br />
| Tfrc or Tfr2?<br />
|-<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
|<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Molecular Function''<br />
|- <br />
| gene<br />
|<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62197Annotation Conf. Call 2016-10-252016-10-19T21:22:03Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! Qualifier<br />
! GO ID/term<br />
! Evidence Code<br />
! With/From<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| gene<br />
|<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
|<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Molecular Function''<br />
|- <br />
| gene<br />
|<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62196Annotation Conf. Call 2016-10-252016-10-19T21:20:12Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! Qualifier<br />
! GO ID/term<br />
! Evidence Code<br />
! With/From<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| gene<br />
|<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|''Cellular Component''<br />
|- <br />
| gene<br />
|<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
|<br />
|<br />
|2a<br />
|-<br />
|gflB<br />
|<br />
|GO:0001965 G-protein alpha-subunit binding<br />
|IPI<br />
|gpaB (DDB_G0276267)<br />
|<br />
|1b<br />
|-<br />
|gflB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|rapA (DDB_G0291237)<br />
|happens_during GO:0001965 G-protein alpha-subunit binding<br />
|s2e + 2b<br />
|-<br />
|gflB<br />
|<br />
|NTR: activation of Rap1 GTPase activity<br />
|IMP<br />
|<br />
|part_of GO:0071320 cellular response to cAMP<br />
|<br />
|-<br />
|gflB<br />
|<br />
|GO:0001965 G-protein alpha-subunit binding<br />
|IPI<br />
|gpaB<br />
|occurs_at SO:0100014 n_terminal_region<br />
|SO term is defining where gflB binds to gpaB - need new relation?<br />
|-<br />
|gflB<br />
|<br />
|GO:0031267 small GTPase binding<br />
|IPI<br />
|RapA<br />
|happens_during, has_direct_input activation of GTPase activity, gpaB<br />
|maybe Rap GTPase binding should be added as child, all others are there<br />
|-<br />
|gflB<br />
|<br />
|GO:0017034 Rap guanyl-nucleotide exchange factor activity<br />
|IDA<br />
|<br />
|has_input, happens_during, occurs_at rapA,activation of GTPase activity, cell cortex<br />
|<br />
|-<br />
|gflB<br />
|<br />
|GO:0005543 phospholipid binding<br />
|IDA<br />
|<br />
|occurs_at SO:0100014 n_terminal_region<br />
|Fig.5SA<br />
|-<br />
|gflB<br />
|<br />
|GO:0001965 G-protein alpha-subunit binding<br />
|IPI<br />
|gpaB<br />
|activated by GppNHp (CHEBI:78408)<br />
|or should this be GTP (CHEBI:15996); pg 460 left column<br />
|-<br />
|gflB<br />
|<br />
|GO:0017034 Rap guanyl-nucleotide exchange factor activity<br />
|IDA<br />
|<br />
|has regulation target: rapA UniProt: P18613<br />
|pg 461 left column<br />
|-<br />
|GflB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GpaB<br />
|<br />
|<br />
|-<br />
|GflB<br />
|<br />
|GO:0005085 guanyl-nucleotide exchange factor activity<br />
|IMP<br />
|<br />
|<br />
|<br />
|-<br />
|GflB<br />
|<br />
|GO:0005085 guanyl-nucleotide exchange factor activity<br />
|IDA<br />
|<br />
|has_input Rap1<br />
|<br />
|-<br />
|GflB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|Rap1<br />
|has_participant GpaB<br />
|depends on Ga2 being bound to GPPnHp<br />
|-<br />
|GflB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GpaB<br />
|<br />
|<br />
|-<br />
|GflB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|RACB, RACL<br />
|<br />
|<br />
|-<br />
|GflB<br />
|<br />
|GO:0005085 guanyl-nucleotide exchange factor activity<br />
|IDA<br />
|<br />
|has_direct_input UniProtKB:P18613<br />
|RAP1 is target<br />
|-<br />
|gpaB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|gflB (DDB_G0286773)<br />
|<br />
|1b<br />
|-<br />
|gpaB<br />
|<br />
|NTR: Ras guanyl-nucleotide exchange factor binding<br />
|IC<br />
|GO:0005515 protein binding<br />
|<br />
|1<br />
|-<br />
|gpaB<br />
|<br />
|GO:0032092 positive regulation of protein binding<br />
|IDA<br />
|<br />
|has_regulation_target AND has_regulation_target gflB (DDB_G0286773) AND rapA (DDB_G0291237<br />
|2b<br />
|-<br />
|gpaB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|<br />
|Possibly a new term for guanylyl-nucleotide exchange factor binding? Also, see above.<br />
|-<br />
|gpaB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|gflB<br />
|part_of GO:0007186 G-protein coupled receptor signaling pathway<br />
|maybe new term 'nucleitide exchange factor binding? Cannot easily annotate that only activated (GTP bound) gpbA binds to gflB<br />
|-<br />
|GpaB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|<br />
|<br />
|-<br />
|GskA<br />
|<br />
|GO:0004674 protein serine/threonine kinase activity<br />
|IDA<br />
|<br />
|has_direct_input GflB<br />
|<br />
|-<br />
|GskA<br />
|<br />
|GO:0004674 protein serine/threonine kinase activity<br />
|IMP<br />
|<br />
|happens_during, part_of, has_regulation_target GO:0071320, GO:1905097, GflB<br />
|full extension: happens_during GO:0071320, part_of GO:1905097, has_regulation_target GflB (GO:0071320 = cellular response to cAMP; GO:1905097 = regulation of guanyl-nucleotide exchange factor activity)<br />
|-<br />
|gskA<br />
|<br />
|GO:0004674 protein serine/threonine kinase activity<br />
|IDA<br />
|<br />
|has_input gflB (DDB_G0286773)<br />
|5d<br />
|-<br />
|GskA<br />
|<br />
|GO:0004674 protein serine/threonine kinase activity<br />
|ISS<br />
|human GSK3b<br />
|has input GflB<br />
|<br />
|-<br />
|GskA<br />
|<br />
|GO:0004674 protein serine/threonine kinase activity<br />
|IDA<br />
|<br />
|has_direct_input UniProtKB:Q54L90<br />
|<br />
|-<br />
|RACB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|<br />
|Fig. S1<br />
|-<br />
|RACL<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|<br />
|Fig. S1<br />
|-<br />
|rapA<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|gflB (DDB_G0286773)<br />
|happens_during GO:0001965 G-protein alpha-subunit binding<br />
|s2e + 2b<br />
|-<br />
|rapA<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|<br />
|<br />
|-<br />
|rapA<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|happens_during activation of GTPase activity<br />
|new term 'nucleitide exchange factor binding?<br />
|-<br />
|-<br />
| ''Cellular Component''<br />
|- <br />
|-<br />
| gflB<br />
|<br />
| GO:0005737 cytoplasm<br />
| IDA<br />
| <br />
|<br />
| unstimulated cells<br />
|-<br />
| gflB<br />
|<br />
| GO:1904269 cell leading edge cell cortex<br />
| IDA<br />
|<br />
|<br />
| unstimulated cells<br />
|-<br />
| gflB<br />
|<br />
| GO:0005938 cell cortex<br />
| IDA<br />
|<br />
| exists_during GO:0071320<br />
| GO:0071320 = cellular response to cAMP; not sure how to capture cytoskeleton dependency, in conventional annotation extensions or LEGO; does the experiment with GflBP1 and LatA show plasma membrane GO:0005886?<br />
|-<br />
| gflB<br />
|<br />
| GO:0005737 cytoplasm<br />
| IDA<br />
|<br />
|<br />
| 5a<br />
|-<br />
| gflB<br />
|<br />
| GO:0005737 cytoplasm<br />
| IDA<br />
|<br />
| exists_during asexual reproduction<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0005938 cell cortex<br />
| IDA<br />
|<br />
| exists_during response to cAMP<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0031252 cell leading edge<br />
| IDA<br />
|<br />
| exists_during chemotaxis to cAMP<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
| exists_during chemotaxis to cAMP<br />
| annotated 'plasma membrane' because of latA + domain expression experiments, also Supp Fig. 5A shows Phospholipid binding (see MF)<br />
|-<br />
| GflB<br />
|<br />
| GO:0005938 cell cortex<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| GflB<br />
|<br />
| GO:0031252 cell leading edge<br />
| IDA<br />
|<br />
| exists_during chemotaxis (GO:0006935)<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0005737 cytoplasm<br />
| IDA<br />
|<br />
|<br />
| pg 462 right column<br />
|-<br />
| gflB<br />
|<br />
| GO:0031252 cell leading edge<br />
| IDA<br />
|<br />
| exists during: cell chemotaxis GO:0060326 <br />
| gradient treatment to induce chemotaxis; pg 462 right column<br />
|-<br />
| gflB<br />
|<br />
| GO:0005938 cell cortex<br />
| IDA<br />
|<br />
| happens during: cellular response to cAMP GO:0071320<br />
| uniform or global treatment with cAMP; pg 462 right column<br />
|-<br />
| gflB<br />
|<br />
| GO:0031256 leading edge membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0031252 cell leading edge<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:1904269 cell leading edge cell cortex<br />
| IDA<br />
|<br />
| localization_dependent_on ?Galpha2<br />
| requires binding of active Galpha<br />
|-<br />
| Raf1<br />
|<br />
| GO:1904269 cell leading edge cell cortex<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| Ral<br />
|<br />
| GO:1904269 cell leading edge cell cortex<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| Rap1<br />
|<br />
| GO:0009279 cell outer membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| Rap1<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| rapA<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
| 3a<br />
|-<br />
| rapA<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| rasG<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
| 3a<br />
|-<br />
| RasG<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| RasG<br />
|<br />
| GO:0009279 cell outer membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| RasG<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=Annotation_Conf._Call_2016-10-25&diff=62195Annotation Conf. Call 2016-10-252016-10-19T21:17:04Z<p>Slaulederkind: /* Annotation Consistency Exercise */</p>
<hr />
<div>=Bluejeans URL: https://bluejeans.com/993661940=<br />
<br />
=Agenda=<br />
<br />
==Meetings==<br />
===Next GOC Meeting - USC, Los Angeles, CA, November 4-6, 2016===<br />
*Link to a registration form is now available for the USC Meeting on the [http://wiki.geneontology.org/index.php/2016_Los_Angeles_GOC_Meeting_Logistics Meeting Logistics Page].<br />
*Register for meeting and dinner, just dinner, just meeting.<br />
*No registration fee for the Noctua workshop.<br />
<br />
==Discussion of Outstanding github Tickets==<br />
*[https://github.com/geneontology/go-ontology/issues/12543 NTR: maintenance of differentiated cell state]<br />
<br />
==Annotation Consistency Exercise==<br />
*[https://www.ncbi.nlm.nih.gov/pubmed/17373738 Evidence for a sequential transfer of iron amongst ferritin, transferrin and transferrin receptor during duodenal absorption of iron in rat and human.]<br />
'''Abstract''' AIM:To elucidate the sequential transfer of iron amongst ferritin, transferrin and transferrin receptor under various iron status conditions.<br />
METHODS:Incorporation of 59Fe into mucosal and luminal proteins was carried out in control WKY rats. The sequential transfer of iron amongst ferritin, transferrin and transferrin receptor was carried out in iron deficient, control and iron overloaded rats. The duodenal proteins were subjected to immunoprecipitation and quantitation by specific ELISA and in situ localization by microautoradiography and immunohistochemistry in tandem duodenal sections. Human duodenal biopsy (n = 36) collected from subjects with differing iron status were also stained for these proteins.<br />
RESULTS:Ferritin was identified as the major protein that incorporated iron in a time-dependent manner in the duodenal mucosa. The concentration of mucosal ferritin was significantly higher in the iron excess group compared to control, iron deficient groups (731.5 +/- 191.96 vs 308.3 +/- 123.36, 731.5 +/- 191.96 vs 256.0 +/- 1.19, P < 0.005), while that of luminal transferrin which was significantly higher than the mucosal did not differ among the groups (10.9 +/- 7.6 vs 0.87 +/- 0.79, 11.1 +/- 10.3 vs 0.80 +/- 1.20, 6.8 +/- 4.7 vs 0.61 +/- 0.63, P < 0.001). In situ grading of proteins and iron, and their superimposition, suggested the occurrence of a sequential transfer of iron. This was demonstrated to occur through the initial binding of iron to luminal transferrin then to absorptive cell surface transferrin receptors. The staining intensity of these proteins varied according to the iron nutrition in humans, with intense staining of transferrin receptor observed in iron deficient subjects.<br />
CONCLUSION:It is concluded that the intestine takes up iron through a sequential transfer involving interaction of luminal transferrin, transferrin-transferrin receptor and ferritin.<br /><br />
<br /><br />
<br />
'''Annotations'''<br />
{| class="wikitable" border="1"<br />
|-<br />
! Gene/Marker Name<br />
! Qualifier<br />
! GO ID/term<br />
! Evidence Code<br />
! With/From<br />
! Annotation Extension <br />
! Comment<br />
|-<br />
|''Biological Process''<br />
|- <br />
| gene<br />
|<br />
| GOID term<br />
| evidence code<br />
|<br />
|<br />
| comment<br />
|-<br />
| gflB<br />
|<br />
| GO:0030837 negative regulation of actin polymerization<br />
| IMP<br />
|<br />
|<br />
| part_of GO:0050920 regulation of chemotaxis? presumably indirect, via effect on rapA activity; will be clearer in LEGO<br />
|-<br />
| gflB<br />
|<br />
| GO:new (cf. GO:0043520) positive regulation of myosin II filament assembly<br />
| IMP<br />
|<br />
|<br />
| part_of GO:0050920 regulation of chemotaxis? presumably indirect, via effect on rapA activity; will be clearer in LEGO<br />
|-<br />
| gflB<br />
|<br />
| GO:0046580 negative regulation of Ras protein signal transduction<br />
| IMP<br />
|<br />
| part_of GO:0071320 cellular response to cAMP<br />
| 2e, 2f<br />
|-<br />
| gflB<br />
|<br />
| GO:0030010 establishment of cell polarity<br />
| IMP<br />
|<br />
| part_of GO:0071320 cellular response to cAMP<br />
| s3b, 3a, s4a<br />
|-<br />
| gflB<br />
|<br />
| NTR: negative regulation of Akt/PKB singalling<br />
| IMP<br />
|<br />
|<br />
| 3b, 3c, s4b<br />
|-<br />
| gflB<br />
|<br />
| NTR: negative regulation of actin polimerization<br />
| IMP<br />
|<br />
| happens_during GO:0043327 chemotaxis to cAMP<br />
| 4a-c<br />
|-<br />
| gflB<br />
|<br />
| NTR: positive regulation of myosin II polimerization<br />
| IMP<br />
|<br />
| happens_during GO:0043327 chemotaxis to cAMP<br />
| 4a-c<br />
|-<br />
| gflB<br />
|<br />
| GO:0043327 chemotaxis to cAMP<br />
| IMP<br />
|<br />
|<br />
| The observed developmental defects seem to be downstream of the cAMP signaling, so maybe in a LEGO diagram the process of chemotaxis to cAMP would have a positive causal relationship to the developmentl processes? Also, 'chemotaxis to cAMP' does not seem to have a relationship to 'response to cAMP' in the ontology. Should it?<br />
|-<br />
| gflB<br />
|<br />
| GO:0071320 cellular response to cAMP<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0043547 positive regulation of GTPase activity<br />
| IMP<br />
|<br />
| has_regulation_target Rap1<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0034260 negative regulation of GTPase activity<br />
| IMP<br />
|<br />
| has_regulation_target RasG|RasB|RasC<br />
| I'm not sure if it's okay to put all of these specific Ras targets when a pan-Ras antibody was used.<br />
|-<br />
| gflB<br />
|<br />
| GO:0007264 small GTPase mediated signal transduction<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0030836 negative regulation of actin filament polymerization<br />
| IMP<br />
|<br />
|<br />
| I'm not sure about making this annotation; if I'm understanding the model correctly, the regulation would be indirect.<br />
|-<br />
| gflB<br />
|<br />
| GO:new positive regulation of myosin II filament assembly<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0090630 activation of GTPase activity<br />
| IMP<br />
|<br />
| has_regulation_target, happens_during, occurs_at rapA, response to cAMP, cell leading edge<br />
| as rap is in ras superfamily, this is the most specific term <br />
|-<br />
| gflB<br />
|<br />
| GO:0046580 negative regulation of Ras protein signal transduction<br />
| IMP<br />
|<br />
| has_regulation_target, happens_during, occurs_at | happens_during rasC, rasG, rasB , response to cAMP, cell leading edge | asexual reproduction<br />
| alternative term: negative regulation of GTPase activity<br />
|-<br />
| gflB<br />
|<br />
| GO:0061118 regulation of positive chemotaxis to cAMP<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0030837 negative regulation of actin filament polymerization<br />
| IMP<br />
|<br />
| happens_during(GO:0051591) response to cAMP ,occurs_at(GO:0005886) plasma membrane <br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0043520 regulation of myosin II filament assembly<br />
| IMP<br />
|<br />
| happens_during(GO:0051591 response to cAMP ,occurs_at(GO:0005886) plasma membrane <br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0030010 establishment of cell polarity<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0071901 negative regulation of protein serine/threonine kinase activity<br />
| IMP<br />
|<br />
| has_input gflB<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0007264 small GTPase mediated signal transductions<br />
| IMP<br />
|<br />
| has_regulation_target pkbA, pkgA<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0030837 negative regulation of actin filament polymerisation<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0043520 regulation of myosin II filament assembly<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0006935 chemotaxis<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0046579 positive regulation of Ras protein signal transduction<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0061122 positive regulation of positive chemotaxis to cAMP<br />
| IMP<br />
|<br />
|<br />
| pg 460 right column<br />
|-<br />
| gflB<br />
|<br />
| GO:0032487 regulation of Rap protein signal transduction<br />
| IMP<br />
|<br />
| happens during: cellular response to cAMP| has input: rapA GO:0071320|UniProt: P18613<br />
| may need to request "positive regulation of Rap signal transduction; pg 461 right column<br />
|-<br />
| gflB<br />
|<br />
| GO:0046580 negative regulation of Ras protein signal transduction<br />
| IMP<br />
|<br />
| happens during: cellular response to cAMP GO:0071320<br />
| no input here as it could be RasG, RasB and or RasC; pg 461 right column<br />
|-<br />
| gflB<br />
|<br />
| GO:0030838 positive regulation of actin filament polymerisation<br />
| IMP<br />
|<br />
| happens during: cellular response to cAMP| occurs at: cell leading GO:0071320|GO:0031252<br />
| pg 462 right column<br />
|-<br />
| gflB<br />
|<br />
| GO:0043520 regulation of myosin II filament assembly<br />
| IMP<br />
|<br />
| happens during: cellular response to cAMP| occurs at: cell leading GO:0071320|GO:0031252<br />
| may need to request "positive regulation of myosin II filament assembly; pg 462 right column<br />
|-<br />
| gflB<br />
|<br />
| GO:0043327 chemotaxis to cAMP<br />
| IMP<br />
|<br />
|<br />
|-<br />
| gflB<br />
| <br />
| GO:0046580 negative regulation of Ras protein signal transduction<br />
| IMP<br />
|<br />
| regulates_o_has_participant RasG<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0046579 positive regulation of Ras protein signal transduction<br />
| IMP<br />
|<br />
| regulates_o_has_participant Rap1<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0030837 negative regulation of actin filament polymerisation<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0043520 regulation of myosin II filament assembly<br />
| IMP<br />
|<br />
|<br />
| ask for positive regulation term<br />
|-<br />
| gflB<br />
|<br />
| GO:0061339 establishment or maintenance of monopolar cell polarity<br />
|<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
| <br />
| GO:0060326 cell chemotaxis<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0046580 negative regulation of Ras protein signal transduction<br />
|<br />
|<br />
| happens_during GO:0060326 cell chemotaxis<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0032487 regulation of Rap protein signal transduction<br />
| IMP<br />
|<br />
| happens_during GO:0060326 cell chemotaxis<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0032487 regulation of Rap protein signal transduction<br />
| IMP<br />
|<br />
| has_regulation_target UniProtKB:P18613<br />
| RAP1 is target<br />
|-<br />
| gpaB<br />
|<br />
| GO:0043327 chemotaxis to cAMP<br />
| IMP<br />
|<br />
|<br />
| Table 1, Figure 1, Movies S1-S3.<br />
|-<br />
| gpaB<br />
|<br />
| GO:0048468 cell development<br />
| IMP<br />
|<br />
|<br />
| S1e<br />
|-<br />
| gpaB<br />
|<br />
| GO:0032092 positive regulation of protein binding<br />
| IDA<br />
|<br />
| has_regulation_target GflB,rapA <br />
| I'm not sure the exact meaning of this annotation is clear, i.e. that gpaB is regulating the binding of GflB to rapA.<br />
|-<br />
| gpaB<br />
|<br />
| GO:1905099 positive regulation of guanyl-nucleotide exchange factor activity<br />
| IDA<br />
|<br />
| has_regulation_target, occurs_at gflB, GO:1904269 cell leading edge cell cortex<br />
|<br />
|-<br />
| gpaB<br />
|<br />
| GO:1905099 positive regulation of guanyl-nucleotide exchange factor activity<br />
| IDA<br />
|<br />
| has regul;ation target: gflB UniProt: Q54L90<br />
|pg 461 left column<br />
|-<br />
| gpaB<br />
|<br />
| GO:1905099 positive regulation of guanyl-nucleotide exchange factor activity<br />
| IDA<br />
|<br />
|<br />
| request a PRO term for the active form?<br />
<br />
|-<br />
| gskA<br />
|<br />
| GO:0006468 protein phosphorylation<br />
| IDA<br />
|<br />
| has_input AND negatively_regulates gflB (DDB_G0286773) AND GO:0072697 protein localization to cell cortex<br />
| 5d, 5e<br />
|-<br />
| gskA<br />
|<br />
| GO:1904777 negative regulation of protein localization to cell cortex<br />
| IMP<br />
|<br />
| has_regulation_target gflB (DDB_G0286773)<br />
| 5e<br />
|-<br />
| gskA<br />
|<br />
| GO:0018105 peptidyl serine phosphorylation<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gskA<br />
|<br />
| GO:0018107 peptidyl threonine phosphorylation<br />
| IMP<br />
|<br />
|<br />
|<br />
|-<br />
| gskA<br />
|<br />
| GO:1904776 regulation of protein localization to cell cortex<br />
| IMP<br />
|<br />
| has_regulation_target GflB<br />
|<br />
|-<br />
| gskA<br />
|<br />
| GO:0006468 protein phosphorylation<br />
| IDA<br />
|<br />
|has_input gflB<br />
|<br />
|-<br />
| gskA<br />
|<br />
| GO:1904776 regulation of protein localization to cell cortex<br />
| IMP<br />
|<br />
| has_regulation_target, occurs_at gflB, leading edge<br />
|<br />
|-<br />
| gskA<br />
|<br />
| GO:0018105 peptidyl-serine phosphorylation<br />
| IMP<br />
|<br />
| has input: gflB UniProt: Q54L90<br />
| pg 464 right column<br />
|-<br />
| gskA<br />
|<br />
| GO:0018107 peptidyl-threonine phosphorylation<br />
| IMP<br />
|<br />
| has input: gflB UniProt: Q54L90<br />
| pg 464 right column<br />
|-<br />
| gskA<br />
|<br />
| GO:1904777 negative regulation of protein localization to cell cortex<br />
| IMP<br />
| <br />
| has regulation target: gflB|happens during: cellular response to cAMP UniProt: Q54L90|GO:0071320<br />
| pg 464 right column<br />
|-<br />
| gskA<br />
|<br />
| GO:0006468 protein phosphorylation<br />
| IMP<br />
|<br />
| has_input GflB<br />
|<br />
|-<br />
| gskA<br />
|<br />
| GO:1902463 protein localization to cell leading edge<br />
|<br />
|<br />
| transports or maintains localization of GflB<br />
|<br />
|-<br />
| rapA<br />
|<br />
| GO:0071320 cellular response to cAMP<br />
| IEP<br />
|<br />
|<br />
|<br />
|-<br />
| rasB<br />
|<br />
| GO:0071320 cellular response to cAMP<br />
| IEP<br />
|<br />
|<br />
| See above comment on pan-Ras antibody.<br />
|-<br />
| rasC<br />
|<br />
| GO:0071320 cellular response to cAMP<br />
| IEP<br />
|<br />
|<br />
| See above comment on pan-Ras antibody.<br />
|-<br />
| rasG<br />
|<br />
| GO:0071320 cellular response to cAMP<br />
| IEP<br />
|<br />
|<br />
| See above comment on pan-Ras antibody.<br />
|-<br />
|-<br />
| ''Molecular Function''<br />
|- <br />
| gflB<br />
|<br />
| GO:0017034 Rap guanyl-nucleotide exchange factor activity<br />
| IDA<br />
|<br />
| has_regulation_target Rap1<br />
|<br />
|-<br />
|gflB<br />
|<br />
|GO:0005515 protein binding<br />
|IDA<br />
|Ga2<br />
|<br />
|<br />
|<br />
|-<br />
|gflB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|Rap1<br />
|<br />
|how to capture "requires presence of active Ga2" in conventional annotation? (I'm not even sure how to do it in LEGO)<br />
|-<br />
|gflB<br />
|NOT<br />
|NTR: Rho GTPase activator activity<br />
|IDA<br />
|<br />
|<br />
|S2b-d<br />
|-<br />
|gflB<br />
|<br />
|GO:0005088 Ras guanyl-nucleotide exchange factor activity<br />
|IMP<br />
|<br />
|<br />
|2a<br />
|-<br />
|gflB<br />
|<br />
|GO:0001965 G-protein alpha-subunit binding<br />
|IPI<br />
|gpaB (DDB_G0276267)<br />
|<br />
|1b<br />
|-<br />
|gflB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|rapA (DDB_G0291237)<br />
|happens_during GO:0001965 G-protein alpha-subunit binding<br />
|s2e + 2b<br />
|-<br />
|gflB<br />
|<br />
|NTR: activation of Rap1 GTPase activity<br />
|IMP<br />
|<br />
|part_of GO:0071320 cellular response to cAMP<br />
|<br />
|-<br />
|gflB<br />
|<br />
|GO:0001965 G-protein alpha-subunit binding<br />
|IPI<br />
|gpaB<br />
|occurs_at SO:0100014 n_terminal_region<br />
|SO term is defining where gflB binds to gpaB - need new relation?<br />
|-<br />
|gflB<br />
|<br />
|GO:0031267 small GTPase binding<br />
|IPI<br />
|RapA<br />
|happens_during, has_direct_input activation of GTPase activity, gpaB<br />
|maybe Rap GTPase binding should be added as child, all others are there<br />
|-<br />
|gflB<br />
|<br />
|GO:0017034 Rap guanyl-nucleotide exchange factor activity<br />
|IDA<br />
|<br />
|has_input, happens_during, occurs_at rapA,activation of GTPase activity, cell cortex<br />
|<br />
|-<br />
|gflB<br />
|<br />
|GO:0005543 phospholipid binding<br />
|IDA<br />
|<br />
|occurs_at SO:0100014 n_terminal_region<br />
|Fig.5SA<br />
|-<br />
|gflB<br />
|<br />
|GO:0001965 G-protein alpha-subunit binding<br />
|IPI<br />
|gpaB<br />
|activated by GppNHp (CHEBI:78408)<br />
|or should this be GTP (CHEBI:15996); pg 460 left column<br />
|-<br />
|gflB<br />
|<br />
|GO:0017034 Rap guanyl-nucleotide exchange factor activity<br />
|IDA<br />
|<br />
|has regulation target: rapA UniProt: P18613<br />
|pg 461 left column<br />
|-<br />
|GflB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GpaB<br />
|<br />
|<br />
|-<br />
|GflB<br />
|<br />
|GO:0005085 guanyl-nucleotide exchange factor activity<br />
|IMP<br />
|<br />
|<br />
|<br />
|-<br />
|GflB<br />
|<br />
|GO:0005085 guanyl-nucleotide exchange factor activity<br />
|IDA<br />
|<br />
|has_input Rap1<br />
|<br />
|-<br />
|GflB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|Rap1<br />
|has_participant GpaB<br />
|depends on Ga2 being bound to GPPnHp<br />
|-<br />
|GflB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GpaB<br />
|<br />
|<br />
|-<br />
|GflB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|RACB, RACL<br />
|<br />
|<br />
|-<br />
|GflB<br />
|<br />
|GO:0005085 guanyl-nucleotide exchange factor activity<br />
|IDA<br />
|<br />
|has_direct_input UniProtKB:P18613<br />
|RAP1 is target<br />
|-<br />
|gpaB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|gflB (DDB_G0286773)<br />
|<br />
|1b<br />
|-<br />
|gpaB<br />
|<br />
|NTR: Ras guanyl-nucleotide exchange factor binding<br />
|IC<br />
|GO:0005515 protein binding<br />
|<br />
|1<br />
|-<br />
|gpaB<br />
|<br />
|GO:0032092 positive regulation of protein binding<br />
|IDA<br />
|<br />
|has_regulation_target AND has_regulation_target gflB (DDB_G0286773) AND rapA (DDB_G0291237<br />
|2b<br />
|-<br />
|gpaB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|<br />
|Possibly a new term for guanylyl-nucleotide exchange factor binding? Also, see above.<br />
|-<br />
|gpaB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|gflB<br />
|part_of GO:0007186 G-protein coupled receptor signaling pathway<br />
|maybe new term 'nucleitide exchange factor binding? Cannot easily annotate that only activated (GTP bound) gpbA binds to gflB<br />
|-<br />
|GpaB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|<br />
|<br />
|-<br />
|GskA<br />
|<br />
|GO:0004674 protein serine/threonine kinase activity<br />
|IDA<br />
|<br />
|has_direct_input GflB<br />
|<br />
|-<br />
|GskA<br />
|<br />
|GO:0004674 protein serine/threonine kinase activity<br />
|IMP<br />
|<br />
|happens_during, part_of, has_regulation_target GO:0071320, GO:1905097, GflB<br />
|full extension: happens_during GO:0071320, part_of GO:1905097, has_regulation_target GflB (GO:0071320 = cellular response to cAMP; GO:1905097 = regulation of guanyl-nucleotide exchange factor activity)<br />
|-<br />
|gskA<br />
|<br />
|GO:0004674 protein serine/threonine kinase activity<br />
|IDA<br />
|<br />
|has_input gflB (DDB_G0286773)<br />
|5d<br />
|-<br />
|GskA<br />
|<br />
|GO:0004674 protein serine/threonine kinase activity<br />
|ISS<br />
|human GSK3b<br />
|has input GflB<br />
|<br />
|-<br />
|GskA<br />
|<br />
|GO:0004674 protein serine/threonine kinase activity<br />
|IDA<br />
|<br />
|has_direct_input UniProtKB:Q54L90<br />
|<br />
|-<br />
|RACB<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|<br />
|Fig. S1<br />
|-<br />
|RACL<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|<br />
|Fig. S1<br />
|-<br />
|rapA<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|gflB (DDB_G0286773)<br />
|happens_during GO:0001965 G-protein alpha-subunit binding<br />
|s2e + 2b<br />
|-<br />
|rapA<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|<br />
|<br />
|-<br />
|rapA<br />
|<br />
|GO:0005515 protein binding<br />
|IPI<br />
|GflB<br />
|happens_during activation of GTPase activity<br />
|new term 'nucleitide exchange factor binding?<br />
|-<br />
|-<br />
| ''Cellular Component''<br />
|- <br />
|-<br />
| gflB<br />
|<br />
| GO:0005737 cytoplasm<br />
| IDA<br />
| <br />
|<br />
| unstimulated cells<br />
|-<br />
| gflB<br />
|<br />
| GO:1904269 cell leading edge cell cortex<br />
| IDA<br />
|<br />
|<br />
| unstimulated cells<br />
|-<br />
| gflB<br />
|<br />
| GO:0005938 cell cortex<br />
| IDA<br />
|<br />
| exists_during GO:0071320<br />
| GO:0071320 = cellular response to cAMP; not sure how to capture cytoskeleton dependency, in conventional annotation extensions or LEGO; does the experiment with GflBP1 and LatA show plasma membrane GO:0005886?<br />
|-<br />
| gflB<br />
|<br />
| GO:0005737 cytoplasm<br />
| IDA<br />
|<br />
|<br />
| 5a<br />
|-<br />
| gflB<br />
|<br />
| GO:0005737 cytoplasm<br />
| IDA<br />
|<br />
| exists_during asexual reproduction<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0005938 cell cortex<br />
| IDA<br />
|<br />
| exists_during response to cAMP<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0031252 cell leading edge<br />
| IDA<br />
|<br />
| exists_during chemotaxis to cAMP<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
| exists_during chemotaxis to cAMP<br />
| annotated 'plasma membrane' because of latA + domain expression experiments, also Supp Fig. 5A shows Phospholipid binding (see MF)<br />
|-<br />
| GflB<br />
|<br />
| GO:0005938 cell cortex<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| GflB<br />
|<br />
| GO:0031252 cell leading edge<br />
| IDA<br />
|<br />
| exists_during chemotaxis (GO:0006935)<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0005737 cytoplasm<br />
| IDA<br />
|<br />
|<br />
| pg 462 right column<br />
|-<br />
| gflB<br />
|<br />
| GO:0031252 cell leading edge<br />
| IDA<br />
|<br />
| exists during: cell chemotaxis GO:0060326 <br />
| gradient treatment to induce chemotaxis; pg 462 right column<br />
|-<br />
| gflB<br />
|<br />
| GO:0005938 cell cortex<br />
| IDA<br />
|<br />
| happens during: cellular response to cAMP GO:0071320<br />
| uniform or global treatment with cAMP; pg 462 right column<br />
|-<br />
| gflB<br />
|<br />
| GO:0031256 leading edge membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:0031252 cell leading edge<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| gflB<br />
|<br />
| GO:1904269 cell leading edge cell cortex<br />
| IDA<br />
|<br />
| localization_dependent_on ?Galpha2<br />
| requires binding of active Galpha<br />
|-<br />
| Raf1<br />
|<br />
| GO:1904269 cell leading edge cell cortex<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| Ral<br />
|<br />
| GO:1904269 cell leading edge cell cortex<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| Rap1<br />
|<br />
| GO:0009279 cell outer membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| Rap1<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| rapA<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
| 3a<br />
|-<br />
| rapA<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| rasG<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
| 3a<br />
|-<br />
| RasG<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| RasG<br />
|<br />
| GO:0009279 cell outer membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|-<br />
| RasG<br />
|<br />
| GO:0005886 plasma membrane<br />
| IDA<br />
|<br />
|<br />
|<br />
|}<br />
<br />
=Minutes=<br />
*On call:<br />
<br />
<br />
[[Category: Annotation Working Group]]</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=59287RGD December 20152015-12-01T17:57:42Z<p>Slaulederkind: /* 5. Other Highlights */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2015 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 40204<br />
| 482,079 (235,178 non-IEA)<br />
| 547,064 (314,567 non-IEA)<br />
| +13%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2014 to December 2015. The number of manual annotations from RGD has increased from 44,967 to 49,791 (+ 4,824 annotations, +11%) and the number of genes with manual annotations has increased from 5,625 to 5,998 (+373, +7%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2015, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: sensory organ disease genes and age-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Liu W, Laulederkind SJ, Hayman GT, Wang SJ, Nigam R, Smith JR, De Pons J, Dwinell MR, Shimoyama M. OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database (Oxford). 2015 Jan 25;2015. pii: bau129. doi: 10.1093/database/bau129. Print 2015.<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2015 Jan;43(Database issue):D743-50. doi: 10.1093/nar/gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind - lightning talk based on poster mentioned below, included information on curating GO data <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind, Weisong Liu, Marek Tutaj, G. Thomas Hayman, Rajni Nigam, Victoria Petri, J. R. Smith, Shur-Jen Wang, Jeff De Pons, M. R. Dwinell, Mary Shimoyama - included information on curating GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 400 - 450 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2014 to December 2015. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on YouTube, Vimeo.com, and rgd.mcw.edu.<br />
<br />
* OLGA (Object List Generator tool) Tutorial- including information on using curated GO data<br />
* Gene Annotator Tutorial- including information on using curated GO data</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=59277RGD December 20152015-12-01T17:16:28Z<p>Slaulederkind: /* 5. Other Highlights */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2015 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 40204<br />
| 482,079 (235,178 non-IEA)<br />
| 547,064 (314,567 non-IEA)<br />
| +13%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2014 to December 2015. The number of manual annotations from RGD has increased from 44,967 to 49,791 (+ 4,824 annotations, +11%) and the number of genes with manual annotations has increased from 5,625 to 5,998 (+373, +7%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2015, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: sensory organ disease genes and age-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Liu W, Laulederkind SJ, Hayman GT, Wang SJ, Nigam R, Smith JR, De Pons J, Dwinell MR, Shimoyama M. OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database (Oxford). 2015 Jan 25;2015. pii: bau129. doi: 10.1093/database/bau129. Print 2015.<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2015 Jan;43(Database issue):D743-50. doi: 10.1093/nar/gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind - lightning talk based on poster mentioned below, included information on curating GO data <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind, Weisong Liu, Marek Tutaj, G. Thomas Hayman, Rajni Nigam, Victoria Petri, J. R. Smith, Shur-Jen Wang, Jeff De Pons, M. R. Dwinell, Mary Shimoyama - included information on curating GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 400 - 450 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2014 to December 2015. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=59267RGD December 20152015-12-01T16:56:01Z<p>Slaulederkind: /* 4. Presentations and publications */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2015 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 40204<br />
| 482,079 (235,178 non-IEA)<br />
| 547,064 (314,567 non-IEA)<br />
| +13%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2014 to December 2015. The number of manual annotations from RGD has increased from 44,967 to 49,791 (+ 4,824 annotations, +11%) and the number of genes with manual annotations has increased from 5,625 to 5,998 (+373, +7%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2015, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: sensory organ disease genes and age-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Liu W, Laulederkind SJ, Hayman GT, Wang SJ, Nigam R, Smith JR, De Pons J, Dwinell MR, Shimoyama M. OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database (Oxford). 2015 Jan 25;2015. pii: bau129. doi: 10.1093/database/bau129. Print 2015.<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2015 Jan;43(Database issue):D743-50. doi: 10.1093/nar/gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind - lightning talk based on poster mentioned below, included information on curating GO data <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind, Weisong Liu, Marek Tutaj, G. Thomas Hayman, Rajni Nigam, Victoria Petri, J. R. Smith, Shur-Jen Wang, Jeff De Pons, M. R. Dwinell, Mary Shimoyama - included information on curating GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=59265RGD December 20152015-12-01T16:54:47Z<p>Slaulederkind: /* 4. Presentations and publications */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2015 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 40204<br />
| 482,079 (235,178 non-IEA)<br />
| 547,064 (314,567 non-IEA)<br />
| +13%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2014 to December 2015. The number of manual annotations from RGD has increased from 44,967 to 49,791 (+ 4,824 annotations, +11%) and the number of genes with manual annotations has increased from 5,625 to 5,998 (+373, +7%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2015, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: sensory organ disease genes and age-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Liu W, Laulederkind SJ, Hayman GT, Wang SJ, Nigam R, Smith JR, De Pons J, Dwinell MR, Shimoyama M. OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database (Oxford). 2015 Jan 25;2015. pii: bau129. doi: 10.1093/database/bau129. Print 2015.<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2015 Jan;43(Database issue):D743-50. doi: 10.1093/nar/gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software <br />
at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind - lightning talk based on poster mentioned below, included information on curating GO data <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software <br />
at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind, Weisong Liu, Marek Tutaj, G. Thomas Hayman, Rajni Nigam, Victoria Petri, J. R. Smith, Shur-Jen Wang, Jeff De Pons, M. R. Dwinell, Mary Shimoyama - included information on curating GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=59264RGD December 20152015-12-01T16:53:53Z<p>Slaulederkind: /* 4. Presentations and publications */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2015 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 40204<br />
| 482,079 (235,178 non-IEA)<br />
| 547,064 (314,567 non-IEA)<br />
| +13%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2014 to December 2015. The number of manual annotations from RGD has increased from 44,967 to 49,791 (+ 4,824 annotations, +11%) and the number of genes with manual annotations has increased from 5,625 to 5,998 (+373, +7%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2015, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: sensory organ disease genes and age-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Liu W, Laulederkind SJ, Hayman GT, Wang SJ, Nigam R, Smith JR, De Pons J, Dwinell MR, Shimoyama M. OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database (Oxford). 2015 Jan 25;2015. pii: bau129. doi: 10.1093/database/bau129. Print 2015.<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2015 Jan;43(Database issue):D743-50. doi: 10.1093/nar/gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software <br />
at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind<br />
- lightning talk based on poster mentioned below, included information on curating GO data <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Eighth International Biocuration Conference, April 23-26, 2015, Friendship Hotel, Beijing, China: "Gene Curation Software <br />
at the Rat Genome Database: Update 2015", Stanley J. F. Laulederkind, Weisong Liu, Marek Tutaj, G. Thomas Hayman, Rajni Nigam, Victoria Petri, J. R. Smith, Shur-Jen Wang, Jeff De Pons, M. R. Dwinell, Mary Shimoyama<br />
- included information on curating GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=59258RGD December 20152015-12-01T16:36:43Z<p>Slaulederkind: /* 4. Presentations and publications */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2015 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 40204<br />
| 482,079 (235,178 non-IEA)<br />
| 547,064 (314,567 non-IEA)<br />
| +13%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2014 to December 2015. The number of manual annotations from RGD has increased from 44,967 to 49,791 (+ 4,824 annotations, +11%) and the number of genes with manual annotations has increased from 5,625 to 5,998 (+373, +7%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2015, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: sensory organ disease genes and age-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Liu W, Laulederkind SJ, Hayman GT, Wang SJ, Nigam R, Smith JR, De Pons J, Dwinell MR, Shimoyama M. OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database (Oxford). 2015 Jan 25;2015. pii: bau129. doi: 10.1093/database/bau129. Print 2015.<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2015 Jan;43(Database issue):D743-50. doi: 10.1093/nar/gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Medical College of Wisconsin Research Day 2014, September 10, 2014, Medical College of Wisconsin, Milwaukee, Wisconsin: "THE RENAL DISEASE PORTAL AT THE RAT GENOME DATABASE", G. Thomas Hayman, Jennifer R. Smith, Stanley Laulederkind, Victoria Petri, Rajni Nigam, Shur-Jen Wang, Jeff De Pons, Marek Tutaj, Weisong Liu, Elizabeth A. Worthey, Melinda R. Dwinell, Mary Shimoyama, Howard J. Jacob - included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=59257RGD December 20152015-12-01T16:35:50Z<p>Slaulederkind: /* 4. Presentations and publications */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2015 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 40204<br />
| 482,079 (235,178 non-IEA)<br />
| 547,064 (314,567 non-IEA)<br />
| +13%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2014 to December 2015. The number of manual annotations from RGD has increased from 44,967 to 49,791 (+ 4,824 annotations, +11%) and the number of genes with manual annotations has increased from 5,625 to 5,998 (+373, +7%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2015, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: sensory organ disease genes and age-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Liu W, Laulederkind SJ, Hayman GT, Wang SJ, Nigam R, Smith JR, De Pons J, Dwinell MR, Shimoyama M. OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database (Oxford). 2015 Jan 25;2015. pii: bau129. doi: 10.1093/database/bau129. Print 2015.<br />
<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2015 Jan;43(Database issue):D743-50. doi: 10.1093/nar/gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Medical College of Wisconsin Research Day 2014, September 10, 2014, Medical College of Wisconsin, Milwaukee, Wisconsin: "THE RENAL DISEASE PORTAL AT THE RAT GENOME DATABASE", G. Thomas Hayman, Jennifer R. Smith, Stanley Laulederkind, Victoria Petri, Rajni Nigam, Shur-Jen Wang, Jeff De Pons, Marek Tutaj, Weisong Liu, Elizabeth A. Worthey, Melinda R. Dwinell, Mary Shimoyama, Howard J. Jacob - included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=59252RGD December 20152015-12-01T16:19:49Z<p>Slaulederkind: /* 3. Methods and strategies for annotation */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2015 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 40204<br />
| 482,079 (235,178 non-IEA)<br />
| 547,064 (314,567 non-IEA)<br />
| +13%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2014 to December 2015. The number of manual annotations from RGD has increased from 44,967 to 49,791 (+ 4,824 annotations, +11%) and the number of genes with manual annotations has increased from 5,625 to 5,998 (+373, +7%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2015, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: sensory organ disease genes and age-related disease genes<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2014 Oct 29. pii: gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Medical College of Wisconsin Research Day 2014, September 10, 2014, Medical College of Wisconsin, Milwaukee, Wisconsin: "THE RENAL DISEASE PORTAL AT THE RAT GENOME DATABASE", G. Thomas Hayman, Jennifer R. Smith, Stanley Laulederkind, Victoria Petri, Rajni Nigam, Shur-Jen Wang, Jeff De Pons, Marek Tutaj, Weisong Liu, Elizabeth A. Worthey, Melinda R. Dwinell, Mary Shimoyama, Howard J. Jacob - included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=59251RGD December 20152015-12-01T16:18:10Z<p>Slaulederkind: /* 2. Annotation progress */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2015 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2014<br />
! Annotations 2015<br />
! % Change<br />
|- <br />
| 40204<br />
| 482,079 (235,178 non-IEA)<br />
| 547,064 (314,567 non-IEA)<br />
| +13%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2014 to December 2015. The number of manual annotations from RGD has increased from 44,967 to 49,791 (+ 4,824 annotations, +11%) and the number of genes with manual annotations has increased from 5,625 to 5,998 (+373, +7%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2014, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: renal disease genes and sensory organ disease genes <br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2014 Oct 29. pii: gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Medical College of Wisconsin Research Day 2014, September 10, 2014, Medical College of Wisconsin, Milwaukee, Wisconsin: "THE RENAL DISEASE PORTAL AT THE RAT GENOME DATABASE", G. Thomas Hayman, Jennifer R. Smith, Stanley Laulederkind, Victoria Petri, Rajni Nigam, Shur-Jen Wang, Jeff De Pons, Marek Tutaj, Weisong Liu, Elizabeth A. Worthey, Melinda R. Dwinell, Mary Shimoyama, Howard J. Jacob - included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=59249RGD December 20152015-12-01T15:52:20Z<p>Slaulederkind: /* 1. Staff working on GOC tasks */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2015 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI GOC grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2013<br />
! Annotations 2014<br />
! % Change<br />
|- <br />
| 39916<br />
| 276,761 (180,448 non-IEA)<br />
| 482,079 (235,178 non-IEA)<br />
| +74%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2013 to December 2014. The number of manual annotations from RGD has increased from 42,335 to 58,561 (+ 16,226 annotations, +38%) and the number of genes with manual annotations has increased from 6113 to 6321 (+208, +3%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2014, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: renal disease genes and sensory organ disease genes <br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2014 Oct 29. pii: gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Medical College of Wisconsin Research Day 2014, September 10, 2014, Medical College of Wisconsin, Milwaukee, Wisconsin: "THE RENAL DISEASE PORTAL AT THE RAT GENOME DATABASE", G. Thomas Hayman, Jennifer R. Smith, Stanley Laulederkind, Victoria Petri, Rajni Nigam, Shur-Jen Wang, Jeff De Pons, Marek Tutaj, Weisong Liu, Elizabeth A. Worthey, Melinda R. Dwinell, Mary Shimoyama, Howard J. Jacob - included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=58555RGD December 20152015-10-01T15:45:55Z<p>Slaulederkind: /* RGD, The Rat Genome Database, December 2015 */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2015 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2013<br />
! Annotations 2014<br />
! % Change<br />
|- <br />
| 39916<br />
| 276,761 (180,448 non-IEA)<br />
| 482,079 (235,178 non-IEA)<br />
| +74%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2013 to December 2014. The number of manual annotations from RGD has increased from 42,335 to 58,561 (+ 16,226 annotations, +38%) and the number of genes with manual annotations has increased from 6113 to 6321 (+208, +3%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2014, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: renal disease genes and sensory organ disease genes <br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2014 Oct 29. pii: gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Medical College of Wisconsin Research Day 2014, September 10, 2014, Medical College of Wisconsin, Milwaukee, Wisconsin: "THE RENAL DISEASE PORTAL AT THE RAT GENOME DATABASE", G. Thomas Hayman, Jennifer R. Smith, Stanley Laulederkind, Victoria Petri, Rajni Nigam, Shur-Jen Wang, Jeff De Pons, Marek Tutaj, Weisong Liu, Elizabeth A. Worthey, Melinda R. Dwinell, Mary Shimoyama, Howard J. Jacob - included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2015&diff=58554RGD December 20152015-10-01T15:43:57Z<p>Slaulederkind: /* RGD, The Rat Genome Database, December 2015 */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2014 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Weisong Liu, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2013<br />
! Annotations 2014<br />
! % Change<br />
|- <br />
| 39916<br />
| 276,761 (180,448 non-IEA)<br />
| 482,079 (235,178 non-IEA)<br />
| +74%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2013 to December 2014. The number of manual annotations from RGD has increased from 42,335 to 58,561 (+ 16,226 annotations, +38%) and the number of genes with manual annotations has increased from 6113 to 6321 (+208, +3%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2014, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: renal disease genes and sensory organ disease genes <br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2014 Oct 29. pii: gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Medical College of Wisconsin Research Day 2014, September 10, 2014, Medical College of Wisconsin, Milwaukee, Wisconsin: "THE RENAL DISEASE PORTAL AT THE RAT GENOME DATABASE", G. Thomas Hayman, Jennifer R. Smith, Stanley Laulederkind, Victoria Petri, Rajni Nigam, Shur-Jen Wang, Jeff De Pons, Marek Tutaj, Weisong Liu, Elizabeth A. Worthey, Melinda R. Dwinell, Mary Shimoyama, Howard J. Jacob - included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=April_2015_GOC_Teleconference_Agenda_and_Logistics&diff=56581April 2015 GOC Teleconference Agenda and Logistics2015-04-01T14:54:08Z<p>Slaulederkind: /* Attendees */</p>
<hr />
<div>[[Category:GO_Consortium_Meetings]]<br />
<br />
==Logistics==<br />
* Call runs April 1, from 11am to 12:30pm EDT<br />
* Call-in information / screen sharing: We will use Bluejeans teleconferencing software for audio and video and WILL NOT use the GO conference line. We will use Bluejeans for screen sharing also. If attendees have a question they should post it on the chat window and they will answered in order.<br />
** Link for the Bluejeans meeting: https://bluejeans.com/626682538<br />
<br />
==Agenda==<br />
===Introduction (11:00 - 11:05) (GO PI's)===<br />
===Discussion of priorities for calendar year 2015 (11:05 - 11:30) (GO PI's)===<br />
* Common Annotation Framework/Environment (CAF/E)<br />
** Goal: LEGO annotation and text mining support in production starting Sept 1 (CAF/E)<br />
** Milestone 1: version of each component that can be used by curation test team<br />
** Milestone 2: Integration of components into Common Annotation Framework/Environment<br />
** Preliminary results on javascript PAINT as part of CAF/E<br />
* Phylogenetic annotation <br />
** meet production goals: annotate 1/3 of genes this grant year<br />
** software for updating annotations to reflect changes in gene sets, experimental annotations and ontology<br />
* Metrics for value/impact of GO data<br />
** Categorize and quantify usage of GO in published papers<br />
** Annotation quality metric and assessment<br />
* Monitoring and assessing our support for users<br />
** User survey<br />
** Website usability study<br />
** Enrichment Analysis: Documentation, UI improvement<br />
<br />
===Talk by Paul Pavlidis, UBC (11:30 - 12:15)===<br />
====The use of GO in data analysis: can we raise the bar?====<br />
* [http://pavlab.chibi.ubc.ca Paul Pavlidis's lab website]<br />
<br />
===Other agenda items (12:15 - 12:30)===<br />
* Update on AmiGO/GO website Behave testing framework (Mary/Seth/Chris)<br />
* Upcoming Consortium meeting in Washington DC<br />
<br />
==Attendees==<br />
Please sign up so we know who can attend.<br />
<br />
<br />
{| {{Prettytable}} class='sortable'<br />
|-<br />
! Name<br />
! Organization<br />
|-<br />
| Rama Balakrishnan<br />
| Stanford University, SGD<br />
|-<br />
|David Hill<br />
|The Jackson Laboratory, MGI<br />
|-<br />
|Harold Drabkin<br />
|The Jackson Laboratory, MGI<br />
|-<br />
|Judy Blake<br />
|The Jackson Laboratory<br />
|-<br />
|Mary Dolan<br />
|The Jackson Laboratory, MGI<br />
|-<br />
| Li Ni<br />
| The Jackson Laboratory, MGI<br />
|-<br />
| Dmitry Sitnikov<br />
| The Jackson Laboratory, MGI<br />
|-<br />
| Karen Christie<br />
| The Jackson Laboratory, MGI<br />
|-<br />
|Kimberly Van Auken<br />
|Cal Tech, Wormbase<br />
|-<br />
|Paul Thomas<br />
|USC<br />
|-<br />
|Huaiyu Mi<br />
|USC<br />
|-<br />
| Moni Munoz-Torres<br />
| Lawrence Berkeley National Lab, BBOP<br />
|-<br />
| Seth Carbon<br />
| Lawrence Berkeley National Lab, BBOP<br />
|-<br />
| Chris Mungall<br />
| Lawrence Berkeley National Lab, BBOP<br />
|-<br />
| Tanya Berardini<br />
| Phoenix Bioinformatics, TAIR<br />
|-<br />
| Eva Huala<br />
| Phoenix Bioinformatics, TAIR<br />
|-<br />
|Donghui Li<br />
| Phoenix Bioinformatics, TAIR<br />
|-<br />
| Doug Howe<br />
| ZFIN<br />
|-<br />
| Sabrina Toro<br />
| ZFIN<br />
|-<br />
| Pascale Gaudet<br />
| GOC / neXtProt<br />
|-<br />
| Marc Feuermann<br />
| Swiss-Prot<br />
|-<br />
| Birgit Meldal<br />
| IntAct / Complex Portal<br />
|-<br />
| Aleks Shypitsyna<br />
| UniProt-GOA, EMBL-EBI<br />
|-<br />
| Penelope Garmiri<br />
| UniProt-GOA, EMBL-EBI<br />
|-<br />
| Rebecca Foulger<br />
| UCL<br />
|-<br />
| Ruth Lovering<br />
| UCL<br />
|-<br />
| Rachael Huntley<br />
| UCL<br />
|-<br />
| Tom Hayman<br />
| RGD<br />
|-<br />
| Mary Shimoyama<br />
| RGD<br />
|-<br />
|Shur-Jen Wang<br />
|RGD<br />
|-<br />
|Stan Laulederkind<br />
|RGD<br />
|-<br />
| Helen Attrill<br />
| FlyBase<br />
|-<br />
| Midori Harris<br />
| PomBase<br />
|-<br />
| Val Wood<br />
| PomBase<br />
|-<br />
| Paola Roncaglia<br />
| EMBL-EBI<br />
|-}</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2014&diff=55332RGD December 20142014-12-02T18:19:36Z<p>Slaulederkind: /* 3. Methods and strategies for annotation */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2014 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Weisong Liu, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2013<br />
! Annotations 2014<br />
! % Change<br />
|- <br />
| 39916<br />
| 276,761 (180,448 non-IEA)<br />
| 482,079 (235,178 non-IEA)<br />
| +74%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2013 to December 2014. The number of manual annotations from RGD has increased from 42,335 to 58,561 (+ 16,226 annotations, +38%) and the number of genes with manual annotations has increased from 6113 to 6321 (+208, +3%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2014, there have been 2 major types of gene datasets curated:<br />
<br />
# disease related: renal disease genes and sensory organ disease genes <br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2014 Oct 29. pii: gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Medical College of Wisconsin Research Day 2014, September 10, 2014, Medical College of Wisconsin, Milwaukee, Wisconsin: "THE RENAL DISEASE PORTAL AT THE RAT GENOME DATABASE", G. Thomas Hayman, Jennifer R. Smith, Stanley Laulederkind, Victoria Petri, Rajni Nigam, Shur-Jen Wang, Jeff De Pons, Marek Tutaj, Weisong Liu, Elizabeth A. Worthey, Melinda R. Dwinell, Mary Shimoyama, Howard J. Jacob - included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2014&diff=55331RGD December 20142014-12-02T18:18:27Z<p>Slaulederkind: /* 5. Other Highlights */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2014 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Weisong Liu, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2013<br />
! Annotations 2014<br />
! % Change<br />
|- <br />
| 39916<br />
| 276,761 (180,448 non-IEA)<br />
| 482,079 (235,178 non-IEA)<br />
| +74%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2013 to December 2014. The number of manual annotations from RGD has increased from 42,335 to 58,561 (+ 16,226 annotations, +38%) and the number of genes with manual annotations has increased from 6113 to 6321 (+208, +3%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2013, there have been 3 major types of gene datasets curated:<br />
<br />
# disease related: renal disease genes and sensory organ disease genes <br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2014 Oct 29. pii: gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Medical College of Wisconsin Research Day 2014, September 10, 2014, Medical College of Wisconsin, Milwaukee, Wisconsin: "THE RENAL DISEASE PORTAL AT THE RAT GENOME DATABASE", G. Thomas Hayman, Jennifer R. Smith, Stanley Laulederkind, Victoria Petri, Rajni Nigam, Shur-Jen Wang, Jeff De Pons, Marek Tutaj, Weisong Liu, Elizabeth A. Worthey, Melinda R. Dwinell, Mary Shimoyama, Howard J. Jacob - included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 50-60 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2013 to December 2014. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 250 times in 2014 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2014&diff=55330RGD December 20142014-12-02T18:07:24Z<p>Slaulederkind: /* 4. Presentations and publications */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2014 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Weisong Liu, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2013<br />
! Annotations 2014<br />
! % Change<br />
|- <br />
| 39916<br />
| 276,761 (180,448 non-IEA)<br />
| 482,079 (235,178 non-IEA)<br />
| +74%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2013 to December 2014. The number of manual annotations from RGD has increased from 42,335 to 58,561 (+ 16,226 annotations, +38%) and the number of genes with manual annotations has increased from 6113 to 6321 (+208, +3%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2013, there have been 3 major types of gene datasets curated:<br />
<br />
# disease related: renal disease genes and sensory organ disease genes <br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 2014 Oct 29. pii: gku1026.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Medical College of Wisconsin Research Day 2014, September 10, 2014, Medical College of Wisconsin, Milwaukee, Wisconsin: "THE RENAL DISEASE PORTAL AT THE RAT GENOME DATABASE", G. Thomas Hayman, Jennifer R. Smith, Stanley Laulederkind, Victoria Petri, Rajni Nigam, Shur-Jen Wang, Jeff De Pons, Marek Tutaj, Weisong Liu, Elizabeth A. Worthey, Melinda R. Dwinell, Mary Shimoyama, Howard J. Jacob - included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 70-100 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2011 to December 2013. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 300 times since April 2013 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2014&diff=55325RGD December 20142014-12-02T17:07:30Z<p>Slaulederkind: /* 3. Methods and strategies for annotation */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2014 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Weisong Liu, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2013<br />
! Annotations 2014<br />
! % Change<br />
|- <br />
| 39916<br />
| 276,761 (180,448 non-IEA)<br />
| 482,079 (235,178 non-IEA)<br />
| +74%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2013 to December 2014. The number of manual annotations from RGD has increased from 42,335 to 58,561 (+ 16,226 annotations, +38%) and the number of genes with manual annotations has increased from 6113 to 6321 (+208, +3%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2013, there have been 3 major types of gene datasets curated:<br />
<br />
# disease related: renal disease genes and sensory organ disease genes <br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease categories, genes involved in particular biological pathways, and genes associated with specific QTLs.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Wang SJ, Laulederkind SJ, Hayman GT, Smith JR, Petri V, Lowry TF, Nigam R, Dwinell MR, Worthey EA, Munzenmaier DH, Shimoyama M, Jacob HJ. Analysis of disease-associated objects at the Rat Genome Database. Database (Oxford). 2013 Jun 21;2013(0):bat046. doi: 10.1093/database/bat046. Print 2013.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Sixth International Biocuration Conference, April 7-10, 2013, Churchill College, Cambridge, UK, : "ONTOLOGY ANALYSES OF DISEASE OBJECTS AT THE RAT GENOME DATABASE", Shur-Jen Wang , Stanley J. F. Laulederkind, G.Thomas Hayman, Timothy Lowry, Rajni Nigam, Victoria Petri, Jennifer Smith, Melinda Dwinell, Mary Shimoyama - included information on curated GO data<br />
# Sixth International Biocuration Conference, April 7-10, 2013, Churchill College, Cambridge, UK, : Cross-Species Functional "Analysis of Gene Sets: The Gene Annotator", Mary Shimoyama, Jeff de Pons, RGD Team – included information on curated GO data<br />
# Rat Genomics & Models, December 11-14, 2013, Cold Spring Harbor, New York: "THE RAT GENOME DATABASE: A NEW PORTAL FOR RENAL DISEASE", Jennifer R. Smith, Mary Shimoyama, Melinda R. Dwinell, Elizabeth A. Worthey, Jeff De Pons, Stanley Laulederkind, Victoria Petri, Rajni Nigam, G. Thomas Hayman, Shur-Jen Wang, Marek Tutaj, Pushkala Jayaraman, Weisong Liu, Howard J. Jacob – included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 70-100 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2011 to December 2013. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 300 times since April 2013 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2014&diff=55324RGD December 20142014-12-02T17:05:19Z<p>Slaulederkind: /* 3. Methods and strategies for annotation */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2014 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Weisong Liu, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2013<br />
! Annotations 2014<br />
! % Change<br />
|- <br />
| 39916<br />
| 276,761 (180,448 non-IEA)<br />
| 482,079 (235,178 non-IEA)<br />
| +74%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2013 to December 2014. The number of manual annotations from RGD has increased from 42,335 to 58,561 (+ 16,226 annotations, +38%) and the number of genes with manual annotations has increased from 6113 to 6321 (+208, +3%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2013, there have been 3 major types of gene datasets curated:<br />
<br />
# disease related: renal disease genes and sensory organ disease genes <br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease, genes involved in particular pathways, and genes associated with the BC4GO project.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Wang SJ, Laulederkind SJ, Hayman GT, Smith JR, Petri V, Lowry TF, Nigam R, Dwinell MR, Worthey EA, Munzenmaier DH, Shimoyama M, Jacob HJ. Analysis of disease-associated objects at the Rat Genome Database. Database (Oxford). 2013 Jun 21;2013(0):bat046. doi: 10.1093/database/bat046. Print 2013.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Sixth International Biocuration Conference, April 7-10, 2013, Churchill College, Cambridge, UK, : "ONTOLOGY ANALYSES OF DISEASE OBJECTS AT THE RAT GENOME DATABASE", Shur-Jen Wang , Stanley J. F. Laulederkind, G.Thomas Hayman, Timothy Lowry, Rajni Nigam, Victoria Petri, Jennifer Smith, Melinda Dwinell, Mary Shimoyama - included information on curated GO data<br />
# Sixth International Biocuration Conference, April 7-10, 2013, Churchill College, Cambridge, UK, : Cross-Species Functional "Analysis of Gene Sets: The Gene Annotator", Mary Shimoyama, Jeff de Pons, RGD Team – included information on curated GO data<br />
# Rat Genomics & Models, December 11-14, 2013, Cold Spring Harbor, New York: "THE RAT GENOME DATABASE: A NEW PORTAL FOR RENAL DISEASE", Jennifer R. Smith, Mary Shimoyama, Melinda R. Dwinell, Elizabeth A. Worthey, Jeff De Pons, Stanley Laulederkind, Victoria Petri, Rajni Nigam, G. Thomas Hayman, Shur-Jen Wang, Marek Tutaj, Pushkala Jayaraman, Weisong Liu, Howard J. Jacob – included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 70-100 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2011 to December 2013. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 300 times since April 2013 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2014&diff=55323RGD December 20142014-12-02T17:03:49Z<p>Slaulederkind: /* 2. Annotation progress */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2014 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Weisong Liu, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2013<br />
! Annotations 2014<br />
! % Change<br />
|- <br />
| 39916<br />
| 276,761 (180,448 non-IEA)<br />
| 482,079 (235,178 non-IEA)<br />
| +74%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2013 to December 2014. The number of manual annotations from RGD has increased from 42,335 to 58,561 (+ 16,226 annotations, +38%) and the number of genes with manual annotations has increased from 6113 to 6321 (+208, +3%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2013, there have been 3 major types of gene datasets curated:<br />
<br />
# disease related: renal disease genes and sensory organ disease genes <br />
# genes which are part of the Biocreative for GO project (BC4GO)<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease, genes involved in particular pathways, and genes associated with the BC4GO project.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Wang SJ, Laulederkind SJ, Hayman GT, Smith JR, Petri V, Lowry TF, Nigam R, Dwinell MR, Worthey EA, Munzenmaier DH, Shimoyama M, Jacob HJ. Analysis of disease-associated objects at the Rat Genome Database. Database (Oxford). 2013 Jun 21;2013(0):bat046. doi: 10.1093/database/bat046. Print 2013.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Sixth International Biocuration Conference, April 7-10, 2013, Churchill College, Cambridge, UK, : "ONTOLOGY ANALYSES OF DISEASE OBJECTS AT THE RAT GENOME DATABASE", Shur-Jen Wang , Stanley J. F. Laulederkind, G.Thomas Hayman, Timothy Lowry, Rajni Nigam, Victoria Petri, Jennifer Smith, Melinda Dwinell, Mary Shimoyama - included information on curated GO data<br />
# Sixth International Biocuration Conference, April 7-10, 2013, Churchill College, Cambridge, UK, : Cross-Species Functional "Analysis of Gene Sets: The Gene Annotator", Mary Shimoyama, Jeff de Pons, RGD Team – included information on curated GO data<br />
# Rat Genomics & Models, December 11-14, 2013, Cold Spring Harbor, New York: "THE RAT GENOME DATABASE: A NEW PORTAL FOR RENAL DISEASE", Jennifer R. Smith, Mary Shimoyama, Melinda R. Dwinell, Elizabeth A. Worthey, Jeff De Pons, Stanley Laulederkind, Victoria Petri, Rajni Nigam, G. Thomas Hayman, Shur-Jen Wang, Marek Tutaj, Pushkala Jayaraman, Weisong Liu, Howard J. Jacob – included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 70-100 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2011 to December 2013. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 300 times since April 2013 across all three video sites)</div>Slaulederkindhttps://wiki.geneontology.org/index.php?title=RGD_December_2014&diff=55322RGD December 20142014-12-02T16:26:11Z<p>Slaulederkind: /* 2. Annotation progress */</p>
<hr />
<div>== RGD, The Rat Genome Database, December 2014 ==<br />
<br />
=== 1. Staff working on GOC tasks ===<br />
<br />
RGD Admin: Mary Shimoyama<br />
<br />
GO Curators: Stan Laulederkind, Tom Hayman, Shur-Jen Wang, Victoria Petri<br />
(~1.5 fte, 0 funded by NHGRI GOC grant)<br />
<br />
IT staff associated with GO related projects such as the development of the online curation tool and of pipelines, the updates/loads of GO ontologies in the database and the generation and submission of RGD Gene Association files: <br />
Weisong Liu, Marek Tutaj, Jeff DePons (1 fte, 0 fte funded by NHGRI grant)<br />
<br />
=== 2. Annotation progress ===<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" align="center"<br />
! Gene Products<br />
! Annotations 2013<br />
! Annotations 2014<br />
! % Change<br />
|- <br />
| 39916<br />
| 276,761 (180,448 non-IEA)<br />
| 482,079 (235,178 non-IEA)<br />
| +74%<br />
|-<br />
|}<br />
<br />
<br />
The table above is based on a review of the GOC gene_association.rgd files from December 2013 to December 2014. The number of manual annotations from RGD has increased from 42,335 to 58,561 (+ 16,226 annotations, +15%) and the number of genes with manual annotations has increased from 5844 to 6113 (+269, +5%).<br />
<br />
=== 3. Methods and strategies for annotation ===<br />
<br />
Because the pipelines for GO annotations are automated and updated weekly, all of the curators’ efforts are involved in manual annotation. Although RGD curators also annotate to other ontologies, approximately 25% of their curation efforts have been related to GO annotations in the past year.<br />
<br />
a. Literature curation: RGD targets gene sets for manual curation and all rat papers published about those genes are curated. In 2013, there have been 3 major types of gene datasets curated:<br />
<br />
# disease related: renal disease genes and sensory organ disease genes <br />
# genes which are part of the Biocreative for GO project (BC4GO)<br />
# genes involved in targeted metabolic, signaling, regulatory, and disease pathways.<br />
<br />
b. Computational annotation strategies:<br />
<br />
# Rat genes manually curated by other groups are brought in electronically from GOA with their associated evidence codes and the originating group acknowledged in the source.<br />
# ISO - RGD is not currently doing manual annotation with ISO. ISO annotations are created through our automated pipelines that map GO annotations from mouse genes over to their Rat orthologs. For each mouse gene that has a confirmed rat ortholog, if the GO annotation to the Mouse gene is of evidence type IDA, IMP, IPI, IGI or IEP then the annotation is loaded onto the rat ortholog as an ISO annotation.<br />
# IEA - rat annotations based on GO mapping to InterPro, Enzyme Commission and Swiss-Prot keywords, are brought in electronically with IEA evidence code from GOA. Annotations from GOA for all categories are updated weekly.<br />
<br />
c. Priorities for annotation: There are several ways in which RGD assigns priorities for the annotation of genes to GO ontology terms. These include: genes associated with targeted disease, genes involved in particular pathways, and genes associated with the BC4GO project.<br />
<br />
=== 4. Presentations and publications ===<br />
<br />
<br />
a. Papers with substantial GO content <br />
<br />
# Wang SJ, Laulederkind SJ, Hayman GT, Smith JR, Petri V, Lowry TF, Nigam R, Dwinell MR, Worthey EA, Munzenmaier DH, Shimoyama M, Jacob HJ. Analysis of disease-associated objects at the Rat Genome Database. Database (Oxford). 2013 Jun 21;2013(0):bat046. doi: 10.1093/database/bat046. Print 2013.<br />
<br />
b. Presentations including Talks and Tutorials and Teaching <br />
<br />
c. Poster presentations with GO content<br />
<br />
# Sixth International Biocuration Conference, April 7-10, 2013, Churchill College, Cambridge, UK, : "ONTOLOGY ANALYSES OF DISEASE OBJECTS AT THE RAT GENOME DATABASE", Shur-Jen Wang , Stanley J. F. Laulederkind, G.Thomas Hayman, Timothy Lowry, Rajni Nigam, Victoria Petri, Jennifer Smith, Melinda Dwinell, Mary Shimoyama - included information on curated GO data<br />
# Sixth International Biocuration Conference, April 7-10, 2013, Churchill College, Cambridge, UK, : Cross-Species Functional "Analysis of Gene Sets: The Gene Annotator", Mary Shimoyama, Jeff de Pons, RGD Team – included information on curated GO data<br />
# Rat Genomics & Models, December 11-14, 2013, Cold Spring Harbor, New York: "THE RAT GENOME DATABASE: A NEW PORTAL FOR RENAL DISEASE", Jennifer R. Smith, Mary Shimoyama, Melinda R. Dwinell, Elizabeth A. Worthey, Jeff De Pons, Stanley Laulederkind, Victoria Petri, Rajni Nigam, G. Thomas Hayman, Shur-Jen Wang, Marek Tutaj, Pushkala Jayaraman, Weisong Liu, Howard J. Jacob – included information on curated GO data<br />
<br />
=== 5. Other Highlights ===<br />
<br />
'''A. GO terms and related contributions by RGD'''<br />
<br />
RGD has contributed 70-100 new terms, new synonyms, or definition/synonym/spelling corrections to GO from December 2011 to December 2013. <br />
<br />
'''B. Annotation outreach and user advocacy efforts'''<br />
<br />
<br />
'''C. Other highlights'''<br />
<br />
Education Video tutorials, available on Scivee.tv, YouTube and Vimeo.com.<br />
<br />
* Gene Annotator Tutorial- including information on using curated GO data (Viewed more than 300 times since April 2013 across all three video sites)</div>Slaulederkind