The InterPro protein families database: the classification resource after 15 years

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ID: 295736
2014
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Abstract
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.
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Authors Alex Mitchell, Hsin-Yu Chang, Louise C. Daugherty, Matthew Fraser, Sarah Hunter, Rodrigo López, Craig McAnulla, Conor McMenamin, Gift Nuka, Sebastien Pesseat, Amaia Sangrador‐Vegas, Maxim Scheremetjew, Cláudia Rato, Siew-Yit Yong, Alex Bateman, Marco Punta, Teresa K. Attwood, Christian Sigrist, Nicole Redaschi, Catherine Rivoire, Ioannis Xénarios, Daniel Kahn, Dominique Guyot, Peer Bork, Ivica Letunić, Julian Gough, Matt E. Oates, Daniel H. Haft, Hongzhan Huang, Darren A. Natale, Cathy Wu, Christine Orengo, Ian Sillitoe, Huaiyu Mi, Paul D. Thomas, ROBERT FINN
Journal Nucleic Acids Research
Year 2014
DOI
10.1093/nar/gku1243
URL
https://academic.oup.com/nar/article-pdf/43/D1/D213/7330324/gku1243.pdf
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