Research Output
BioGRID: A Resource for Studying Biological Interactions in Yeast: Table 1.
  The Biological General Repository for Interaction Datasets (BioGRID) is a freely available public database that provides the biological and biomedical research communities with curated protein and genetic interaction data. Structured experimental evidence codes, an intuitive search interface, and visualization tools enable the discovery of individual gene, protein, or biological network function. BioGRID houses interaction data for the major model organism species—including yeast, nematode, fly, zebrafish, mouse, and human—with particular emphasis on the budding yeast Saccharomyces cerevisiae and the fission yeast Schizosaccharomyces pombe as pioneer eukaryotic models for network biology. BioGRID has achieved comprehensive curation coverage of the entire literature for these two major yeast models, which is actively maintained through monthly curation updates. As of September 2015, BioGRID houses approximately 335,400 biological interactions for budding yeast and approximately 67,800 interactions for fission yeast. BioGRID also supports an integrated posttranslational modification (PTM) viewer that incorporates more than 20,100 yeast phosphorylation sites curated through its sister database, the PhosphoGRID.

  • Type:

    Article

  • Date:

    04 January 2016

  • Publication Status:

    Published

  • Publisher

    Cold Spring Harbor Laboratory Press

  • DOI:

    10.1101/pdb.top080754

  • Cross Ref:

    10.1101/pdb.top080754

  • ISSN:

    1940-3402

  • Library of Congress:

    QH301 Biology

  • Dewey Decimal Classification:

    572 Biochemistry

  • Funders:

    Biotechnology and Biological Sciences Research Council; National Institutes of Health; Canadian Institutes of Health Research

Citation

Oughtred, R., Chatr-aryamontri, A., Breitkreutz, B., Chang, C. S., Rust, J. M., Theesfeld, C. L., …Tyers, M. (2016). BioGRID: A Resource for Studying Biological Interactions in Yeast: Table 1. Cold Spring Harbor protocols, 2016(1), pdb.top080754. https://doi.org/10.1101/pdb.top080754

Authors

Keywords

Biochemistry, Genetics and Molecular Biology(all)

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