InterPro in 2019: improving coverage, classification and access to protein sequence annotations

Alex Mitchell(European Bioinformatics Institute), Teresa K. Attwood(University of Manchester), Patricia C. Babbitt(University of California, San Francisco), Matthias Blum(European Bioinformatics Institute), Peer Bork(European Molecular Biology Laboratory), Alan Bridge(SIB Swiss Institute of Bioinformatics), Shoshana Brown(University of California, San Francisco), Hsin-Yu Chang(European Bioinformatics Institute), Sara El-Gebali(European Bioinformatics Institute), Matthew Fraser(European Bioinformatics Institute), Julian Gough(MRC Laboratory of Molecular Biology), David R Haft(J. Craig Venter Institute), Hongzhan Huang(University of Delaware), Ivica Letunić(Biobyte Solutions (Germany)), Rodrigo López(European Bioinformatics Institute), Aurélien Luciani(European Bioinformatics Institute), Fábio Madeira(European Bioinformatics Institute), Aron Marchler‐Bauer(National Center for Biotechnology Information), Huaiyu Mi(University of Southern California), Darren A. Natale(Georgetown University), Marco Necci(Fondazione Edmund Mach), Gift Nuka(European Bioinformatics Institute), Christine Orengo(Institute of Structural and Molecular Biology), Arun Prasad Pandurangan(MRC Laboratory of Molecular Biology), Typhaine Paysan‐Lafosse(European Bioinformatics Institute), Sebastien Pesseat(European Bioinformatics Institute), Simon Potter(European Bioinformatics Institute), Matloob Qureshi(European Bioinformatics Institute), Neil D. Rawlings(European Bioinformatics Institute), Nicole Redaschi(SIB Swiss Institute of Bioinformatics), Lorna Richardson(European Bioinformatics Institute), Catherine Rivoire(SIB Swiss Institute of Bioinformatics), Gustavo A Salazar(European Bioinformatics Institute), Amaia Sangrador‐Vegas(European Bioinformatics Institute), Christian J A Sigrist(SIB Swiss Institute of Bioinformatics), Ian Sillitoe(Institute of Structural and Molecular Biology), Granger G. Sutton(J. Craig Venter Institute), Narmada Thanki(National Center for Biotechnology Information), Paul D. Thomas(University of Southern California), Silvio C. E. Tosatto(University of Padua), Siew-Yit Yong(European Bioinformatics Institute), ROBERT FINN(European Bioinformatics Institute)
Nucleic Acids Research
October 22, 2018
10.1093/nar/gky1100
Cited by 1,534Open Access
Full Text

Abstract

The InterPro database (http://www.ebi.ac.uk/interpro/) classifies protein sequences into families and predicts the presence of functionally important domains and sites. Here, we report recent developments with InterPro (version 70.0) and its associated software, including an 18% growth in the size of the database in terms on new InterPro entries, updates to content, the inclusion of an additional entry type, refined modelling of discontinuous domains, and the development of a new programmatic interface and website. These developments extend and enrich the information provided by InterPro, and provide greater flexibility in terms of data access. We also show that InterPro's sequence coverage has kept pace with the growth of UniProtKB, and discuss how our evaluation of residue coverage may help guide future curation activities.

Related Papers

Gene Ontology: tool for the unification of biology
Michael Ashburner, Catherine A. Ball, Judith A. Blake et al.|Nature Genetics|2000|44.4k
Predicting transmembrane protein topology with a hidden markov model: application to complete genomes11Edited by F. Cohen
Anders Krogh, B. Larsson, Gunnar von Heijne et al.|Journal of Molecular Biology|2001|13k
InterProScan 5: genome-scale protein function classification
Philip Jones, David Binns, Hsin-Yu Chang et al.|Bioinformatics|2014|9.9k
UniProt: the Universal Protein knowledgebase
Rolf Apweiler|Nucleic Acids Research|2003|7.8k
Predicting Coiled Coils from Protein Sequences
Andrei N. Lupas, Marc Van Dyke, Jeff Stock|Science|1991|4k