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Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation
InterPro amalgamates predictive protein signatures from a number of well-known partner databases into a single resource. To aid with interpretation of results, InterPro entries are manually annotated with terms from the Gene Ontology (GO). The InterPro2GO mappings are comprised of the cross-referenc...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3270475/ https://www.ncbi.nlm.nih.gov/pubmed/22301074 http://dx.doi.org/10.1093/database/bar068 |
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author | Burge, Sarah Kelly, Elizabeth Lonsdale, David Mutowo-Muellenet, Prudence McAnulla, Craig Mitchell, Alex Sangrador-Vegas, Amaia Yong, Siew-Yit Mulder, Nicola Hunter, Sarah |
author_facet | Burge, Sarah Kelly, Elizabeth Lonsdale, David Mutowo-Muellenet, Prudence McAnulla, Craig Mitchell, Alex Sangrador-Vegas, Amaia Yong, Siew-Yit Mulder, Nicola Hunter, Sarah |
author_sort | Burge, Sarah |
collection | PubMed |
description | InterPro amalgamates predictive protein signatures from a number of well-known partner databases into a single resource. To aid with interpretation of results, InterPro entries are manually annotated with terms from the Gene Ontology (GO). The InterPro2GO mappings are comprised of the cross-references between these two resources and are the largest source of GO annotation predictions for proteins. Here, we describe the protocol by which InterPro curators integrate GO terms into the InterPro database. We discuss the unique challenges involved in integrating specific GO terms with entries that may describe a diverse set of proteins, and we illustrate, with examples, how InterPro hierarchies reflect GO terms of increasing specificity. We describe a revised protocol for GO mapping that enables us to assign GO terms to domains based on the function of the individual domain, rather than the function of the families in which the domain is found. We also discuss how taxonomic constraints are dealt with and those cases where we are unable to add any appropriate GO terms. Expert manual annotation of InterPro entries with GO terms enables users to infer function, process or subcellular information for uncharacterized sequences based on sequence matches to predictive models. Database URL: http://www.ebi.ac.uk/interpro. The complete InterPro2GO mappings are available at: ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/external2go/interpro2go |
format | Online Article Text |
id | pubmed-3270475 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-32704752012-02-02 Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation Burge, Sarah Kelly, Elizabeth Lonsdale, David Mutowo-Muellenet, Prudence McAnulla, Craig Mitchell, Alex Sangrador-Vegas, Amaia Yong, Siew-Yit Mulder, Nicola Hunter, Sarah Database (Oxford) Original Article InterPro amalgamates predictive protein signatures from a number of well-known partner databases into a single resource. To aid with interpretation of results, InterPro entries are manually annotated with terms from the Gene Ontology (GO). The InterPro2GO mappings are comprised of the cross-references between these two resources and are the largest source of GO annotation predictions for proteins. Here, we describe the protocol by which InterPro curators integrate GO terms into the InterPro database. We discuss the unique challenges involved in integrating specific GO terms with entries that may describe a diverse set of proteins, and we illustrate, with examples, how InterPro hierarchies reflect GO terms of increasing specificity. We describe a revised protocol for GO mapping that enables us to assign GO terms to domains based on the function of the individual domain, rather than the function of the families in which the domain is found. We also discuss how taxonomic constraints are dealt with and those cases where we are unable to add any appropriate GO terms. Expert manual annotation of InterPro entries with GO terms enables users to infer function, process or subcellular information for uncharacterized sequences based on sequence matches to predictive models. Database URL: http://www.ebi.ac.uk/interpro. The complete InterPro2GO mappings are available at: ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/external2go/interpro2go Oxford University Press 2012-02-01 /pmc/articles/PMC3270475/ /pubmed/22301074 http://dx.doi.org/10.1093/database/bar068 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Burge, Sarah Kelly, Elizabeth Lonsdale, David Mutowo-Muellenet, Prudence McAnulla, Craig Mitchell, Alex Sangrador-Vegas, Amaia Yong, Siew-Yit Mulder, Nicola Hunter, Sarah Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation |
title | Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation |
title_full | Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation |
title_fullStr | Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation |
title_full_unstemmed | Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation |
title_short | Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation |
title_sort | manual go annotation of predictive protein signatures: the interpro approach to go curation |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3270475/ https://www.ncbi.nlm.nih.gov/pubmed/22301074 http://dx.doi.org/10.1093/database/bar068 |
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