71
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The BioGRID interaction database: 2019 update

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The Biological General Repository for Interaction Datasets (BioGRID: https://thebiogrid.org) is an open access database dedicated to the curation and archival storage of protein, genetic and chemical interactions for all major model organism species and humans. As of September 2018 (build 3.4.164), BioGRID contains records for 1 598 688 biological interactions manually annotated from 55 809 publications for 71 species, as classified by an updated set of controlled vocabularies for experimental detection methods. BioGRID also houses records for >700 000 post-translational modification sites. BioGRID now captures chemical interaction data, including chemical–protein interactions for human drug targets drawn from the DrugBank database and manually curated bioactive compounds reported in the literature. A new dedicated aspect of BioGRID annotates genome-wide CRISPR/Cas9-based screens that report gene–phenotype and gene–gene relationships. An extension of the BioGRID resource called the Open Repository for CRISPR Screens (ORCS) database ( https://orcs.thebiogrid.org) currently contains over 500 genome-wide screens carried out in human or mouse cell lines. All data in BioGRID is made freely available without restriction, is directly downloadable in standard formats and can be readily incorporated into existing applications via our web service platforms. BioGRID data are also freely distributed through partner model organism databases and meta-databases.

          Related collections

          Most cited references53

          • Record: found
          • Abstract: found
          • Article: not found

          A global genetic interaction network maps a wiring diagram of cellular function.

          We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            The BioGRID interaction database: 2017 update

            The Biological General Repository for Interaction Datasets (BioGRID: https://thebiogrid.org) is an open access database dedicated to the annotation and archival of protein, genetic and chemical interactions for all major model organism species and humans. As of September 2016 (build 3.4.140), the BioGRID contains 1 072 173 genetic and protein interactions, and 38 559 post-translational modifications, as manually annotated from 48 114 publications. This dataset represents interaction records for 66 model organisms and represents a 30% increase compared to the previous 2015 BioGRID update. BioGRID curates the biomedical literature for major model organism species, including humans, with a recent emphasis on central biological processes and specific human diseases. To facilitate network-based approaches to drug discovery, BioGRID now incorporates 27 501 chemical–protein interactions for human drug targets, as drawn from the DrugBank database. A new dynamic interaction network viewer allows the easy navigation and filtering of all genetic and protein interaction data, as well as for bioactive compounds and their established targets. BioGRID data are directly downloadable without restriction in a variety of standardized formats and are freely distributed through partner model organism databases and meta-databases.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology

              BindingDB, www.bindingdb.org, is a publicly accessible database of experimental protein-small molecule interaction data. Its collection of over a million data entries derives primarily from scientific articles and, increasingly, US patents. BindingDB provides many ways to browse and search for data of interest, including an advanced search tool, which can cross searches of multiple query types, including text, chemical structure, protein sequence and numerical affinities. The PDB and PubMed provide links to data in BindingDB, and vice versa; and BindingDB provides links to pathway information, the ZINC catalog of available compounds, and other resources. The BindingDB website offers specialized tools that take advantage of its large data collection, including ones to generate hypotheses for the protein targets bound by a bioactive compound, and for the compounds bound by a new protein of known sequence; and virtual compound screening by maximal chemical similarity, binary kernel discrimination, and support vector machine methods. Specialized data sets are also available, such as binding data for hundreds of congeneric series of ligands, drawn from BindingDB and organized for use in validating drug design methods. BindingDB offers several forms of programmatic access, and comes with extensive background material and documentation. Here, we provide the first update of BindingDB since 2007, focusing on new and unique features and highlighting directions of importance to the field as a whole.
                Bookmark

                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2019
                24 November 2018
                24 November 2018
                : 47
                : Database issue , Database issue
                : D529-D541
                Affiliations
                [1 ]Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
                [2 ]The Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario M5G 1X5, Canada
                [3 ]Arthur and Sonia Labatt Brain Tumor Research Center and Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
                [4 ]Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, Quebec H3C 3J7, Canada
                Author notes
                To whom correspondence should be addressed. Tel: +1 514 343 6668; Email: md.tyers@ 123456umontreal.ca

                The authors wish it to be known that, in their opinion, the first three authors should be regarded as joint first authors.

                Author information
                http://orcid.org/0000-0002-9713-9994
                Article
                gky1079
                10.1093/nar/gky1079
                6324058
                30476227
                1976093c-916d-4d13-b2bd-dbccee56b18c
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 22 November 2018
                : 15 October 2018
                : 23 September 2018
                Page count
                Pages: 13
                Funding
                Funded by: National Institutes of Health Office of Research Infrastructure
                Award ID: R01OD010929
                Funded by: National Institutes of Health 10.13039/100000002
                Award ID: OT3TR002026
                Funded by: Genomics Institute Largescale Applied Proteomics
                Award ID: OGI-069
                Categories
                Database Issue

                Genetics
                Genetics

                Comments

                Comment on this article