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BioGRID


NAR Molecular Biology Database Collection entry number 800
Tyers, Mike; Chatr Aryamontri, Andrew; Breitkreutz, Bobby-Joe; Heineke, Sven; Boucher, Lorrie; 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, Mike; Oughtred, Rose; Dolinski, Kara
1Ontario Cancer Institute, Princess Margaret Hospital, 610 University Avenue, Toronto, Ontario M5G 2M9, Canada
2Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto Ontario M5G 1X5, Canada
3Department of Medical Genetics and Microbiology, University of Toronto, Toronto, Ontario M5S 1A8, Canada

Database Description

Access to unified datasets of protein and genetic interactions is critical for interrogation of gene/protein function and analysis of global network properties. BioGRID is a freely accessible database of physical and genetic interactions available at http://www.thebiogrid.org. BioGRID release version 2.0 includes more than 116,000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens. An internally hyper-linked web interface allows for rapid search and retrieval of interaction data. Full or user-defined datasets are freely downloadable as tab-delimited text files and PSI-MI XML. Pre-computed graphical layouts of interactions are available in a variety of file formats. User-customized graphs with embedded protein, gene and interaction attributes can be constructed with a visualization system called Osprey that is dynamically linked to the BioGRID.
Over 30,000 protein and genetic interactions have been added from 5,778 sources through exhaustive curation of the S. cerevisiae primary literature (Reguly et al, submitted). An analogous systematically curated set of interactions compiled from the Schizosaccharomyces pombe (fission yeast) literature will also be deposited shortly. Selected physical interaction datasets for TGF-b, TOR and cancer networks in mammalian cells will also be deposited in the near future. A new quantitative genetic interaction experimental descriptor has been added to accommodate recent Epistatic Mini-Array Profiles (E-MAP) and other forms of quantitative genetic interaction data generated in S. cerevisiae.


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