Andrew Chatr-aryamontri
The BioGRID interaction database: 2015 update
Chatr-aryamontri, Andrew; Breitkreutz, Bobby-Joe; Oughtred, Rose; Boucher, Lorrie; Heinicke, Sven; Chen, Daici; Stark, Chris; Breitkreutz, Ashton; Kolas, Nadine; O'Donnell, Lara; Reguly, Teresa; Nixon, Julie; Ramage, Lindsay; Winter, Andrew; Sellam, Adnane; Chang, Christie; Hirschman, Jodi; Theesfeld, Chandra; Rust, Jennifer; Livstone, Michael S.; Dolinski, Kara; Tyers, Mike
Authors
Bobby-Joe Breitkreutz
Rose Oughtred
Lorrie Boucher
Sven Heinicke
Daici Chen
Chris Stark
Ashton Breitkreutz
Nadine Kolas
Lara O'Donnell
Teresa Reguly
Julie Nixon
Lindsay Ramage
Andrew Winter
Adnane Sellam
Christie Chang
Jodi Hirschman
Chandra Theesfeld
Jennifer Rust
Michael S. Livstone
Kara Dolinski
Mike Tyers
Abstract
The Biological General Repository for Interaction Datasets (BioGRID: http://thebiogrid.org) is an open access database that houses genetic and protein interactions curated from the primary biomedical literature for all major model organism species and humans. As of September 2014, the BioGRID contains 749 912 interactions as drawn from 43 149 publications that represent 30 model organisms. This interaction count represents a 50% increase compared to our previous 2013 BioGRID update. BioGRID data are freely distributed through partner model organism databases and meta-databases and are directly downloadable in a variety of formats. In addition to general curation of the published literature for the major model species, BioGRID undertakes themed curation projects in areas of particular relevance for biomedical sciences, such as the ubiquitin-proteasome system and various human disease-associated interaction networks. BioGRID curation is coordinated through an Interaction Management System (IMS) that facilitates the compilation interaction records through structured evidence codes, phenotype ontologies, and gene annotation. The BioGRID architecture has been improved in order to support a broader range of interaction and post-translational modification types, to allow the representation of more complex multi-gene/protein interactions, to account for cellular phenotypes through structured ontologies, to expedite curation through semi-automated text-mining approaches, and to enhance curation quality control.
Citation
Chatr-aryamontri, A., Breitkreutz, B.-J., Oughtred, R., Boucher, L., Heinicke, S., Chen, D., Stark, C., Breitkreutz, A., Kolas, N., O'Donnell, L., Reguly, T., Nixon, J., Ramage, L., Winter, A., Sellam, A., Chang, C., Hirschman, J., Theesfeld, C., Rust, J., Livstone, M. S., …Tyers, M. (2015). The BioGRID interaction database: 2015 update. Nucleic Acids Research, 43(D1), D470-D478. https://doi.org/10.1093/nar/gku1204
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 5, 2014 |
Online Publication Date | Nov 26, 2014 |
Publication Date | Jan 28, 2015 |
Deposit Date | Mar 25, 2017 |
Publicly Available Date | Mar 26, 2017 |
Journal | Nucleic Acids Research |
Print ISSN | 0305-1048 |
Electronic ISSN | 1362-4962 |
Publisher | Oxford University Press |
Peer Reviewed | Peer Reviewed |
Volume | 43 |
Issue | D1 |
Pages | D470-D478 |
DOI | https://doi.org/10.1093/nar/gku1204 |
Keywords | BIOGRID, protein interactions, bioinformatics, structured ontology, text-mining, |
Public URL | http://researchrepository.napier.ac.uk/Output/819897 |
Contract Date | Mar 25, 2017 |
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