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The InterPro protein families database: the classification resource after 15 years
The InterPro database (http://www.ebi.ac.uk/interpro/) is a freely available resource that can be used to classify sequences into protein families and to predict the presence of important domains and sites. Central to the InterPro database are predictive models, known as signatures, from a range of...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4383996/ https://www.ncbi.nlm.nih.gov/pubmed/25428371 http://dx.doi.org/10.1093/nar/gku1243 |
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author | Mitchell, Alex Chang, Hsin-Yu Daugherty, Louise Fraser, Matthew Hunter, Sarah Lopez, Rodrigo McAnulla, Craig McMenamin, Conor Nuka, Gift Pesseat, Sebastien Sangrador-Vegas, Amaia Scheremetjew, Maxim Rato, Claudia Yong, Siew-Yit Bateman, Alex Punta, Marco Attwood, Teresa K. Sigrist, Christian J.A. Redaschi, Nicole Rivoire, Catherine Xenarios, Ioannis Kahn, Daniel Guyot, Dominique Bork, Peer Letunic, Ivica Gough, Julian Oates, Matt Haft, Daniel Huang, Hongzhan Natale, Darren A. Wu, Cathy H. Orengo, Christine Sillitoe, Ian Mi, Huaiyu Thomas, Paul D. Finn, Robert D. |
author_facet | Mitchell, Alex Chang, Hsin-Yu Daugherty, Louise Fraser, Matthew Hunter, Sarah Lopez, Rodrigo McAnulla, Craig McMenamin, Conor Nuka, Gift Pesseat, Sebastien Sangrador-Vegas, Amaia Scheremetjew, Maxim Rato, Claudia Yong, Siew-Yit Bateman, Alex Punta, Marco Attwood, Teresa K. Sigrist, Christian J.A. Redaschi, Nicole Rivoire, Catherine Xenarios, Ioannis Kahn, Daniel Guyot, Dominique Bork, Peer Letunic, Ivica Gough, Julian Oates, Matt Haft, Daniel Huang, Hongzhan Natale, Darren A. Wu, Cathy H. Orengo, Christine Sillitoe, Ian Mi, Huaiyu Thomas, Paul D. Finn, Robert D. |
author_sort | Mitchell, Alex |
collection | PubMed |
description | The InterPro database (http://www.ebi.ac.uk/interpro/) is a freely available resource that can be used to classify sequences into protein families and to predict the presence of important domains and sites. Central to the InterPro database are predictive models, known as signatures, from a range of different protein family databases that have different biological focuses and use different methodological approaches to classify protein families and domains. InterPro integrates these signatures, capitalizing on the respective strengths of the individual databases, to produce a powerful protein classification resource. Here, we report on the status of InterPro as it enters its 15th year of operation, and give an overview of new developments with the database and its associated Web interfaces and software. In particular, the new domain architecture search tool is described and the process of mapping of Gene Ontology terms to InterPro is outlined. We also discuss the challenges faced by the resource given the explosive growth in sequence data in recent years. InterPro (version 48.0) contains 36 766 member database signatures integrated into 26 238 InterPro entries, an increase of over 3993 entries (5081 signatures), since 2012. |
format | Online Article Text |
id | pubmed-4383996 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-43839962015-04-08 The InterPro protein families database: the classification resource after 15 years Mitchell, Alex Chang, Hsin-Yu Daugherty, Louise Fraser, Matthew Hunter, Sarah Lopez, Rodrigo McAnulla, Craig McMenamin, Conor Nuka, Gift Pesseat, Sebastien Sangrador-Vegas, Amaia Scheremetjew, Maxim Rato, Claudia Yong, Siew-Yit Bateman, Alex Punta, Marco Attwood, Teresa K. Sigrist, Christian J.A. Redaschi, Nicole Rivoire, Catherine Xenarios, Ioannis Kahn, Daniel Guyot, Dominique Bork, Peer Letunic, Ivica Gough, Julian Oates, Matt Haft, Daniel Huang, Hongzhan Natale, Darren A. Wu, Cathy H. Orengo, Christine Sillitoe, Ian Mi, Huaiyu Thomas, Paul D. Finn, Robert D. Nucleic Acids Res Database Issue The InterPro database (http://www.ebi.ac.uk/interpro/) is a freely available resource that can be used to classify sequences into protein families and to predict the presence of important domains and sites. Central to the InterPro database are predictive models, known as signatures, from a range of different protein family databases that have different biological focuses and use different methodological approaches to classify protein families and domains. InterPro integrates these signatures, capitalizing on the respective strengths of the individual databases, to produce a powerful protein classification resource. Here, we report on the status of InterPro as it enters its 15th year of operation, and give an overview of new developments with the database and its associated Web interfaces and software. In particular, the new domain architecture search tool is described and the process of mapping of Gene Ontology terms to InterPro is outlined. We also discuss the challenges faced by the resource given the explosive growth in sequence data in recent years. InterPro (version 48.0) contains 36 766 member database signatures integrated into 26 238 InterPro entries, an increase of over 3993 entries (5081 signatures), since 2012. Oxford University Press 2014-11-26 2015-01-28 /pmc/articles/PMC4383996/ /pubmed/25428371 http://dx.doi.org/10.1093/nar/gku1243 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Issue Mitchell, Alex Chang, Hsin-Yu Daugherty, Louise Fraser, Matthew Hunter, Sarah Lopez, Rodrigo McAnulla, Craig McMenamin, Conor Nuka, Gift Pesseat, Sebastien Sangrador-Vegas, Amaia Scheremetjew, Maxim Rato, Claudia Yong, Siew-Yit Bateman, Alex Punta, Marco Attwood, Teresa K. Sigrist, Christian J.A. Redaschi, Nicole Rivoire, Catherine Xenarios, Ioannis Kahn, Daniel Guyot, Dominique Bork, Peer Letunic, Ivica Gough, Julian Oates, Matt Haft, Daniel Huang, Hongzhan Natale, Darren A. Wu, Cathy H. Orengo, Christine Sillitoe, Ian Mi, Huaiyu Thomas, Paul D. Finn, Robert D. The InterPro protein families database: the classification resource after 15 years |
title | The InterPro protein families database: the classification resource after 15 years |
title_full | The InterPro protein families database: the classification resource after 15 years |
title_fullStr | The InterPro protein families database: the classification resource after 15 years |
title_full_unstemmed | The InterPro protein families database: the classification resource after 15 years |
title_short | The InterPro protein families database: the classification resource after 15 years |
title_sort | interpro protein families database: the classification resource after 15 years |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4383996/ https://www.ncbi.nlm.nih.gov/pubmed/25428371 http://dx.doi.org/10.1093/nar/gku1243 |
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