The BioGRID interaction database: 2015 update

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ID: 300924
2014
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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.
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openalex_W2915975108 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Andrew Chatr‐aryamontri, Bobby‐Joe Breitkreutz, Rose Oughtred, Lorrie Boucher, Sven Heinicke, Daici Chen, Chris Stark, Ashton Breitkreutz, Nadine K. Kolas, Lara O’Donnell, Teresa Reguly, Julie Nixon, Lindsay Ramage, Andrew Winter, Adnane Sellam, Christie Chang, Jodi Hirschman, Chandra L. Theesfeld, Jennifer Rust, Michael Livstone, Kara Dolinski, Mike Tyers
Journal Nucleic Acids Research
Year 2014
DOI
10.1093/nar/gku1204
URL
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