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Database Commons - BioGRID

BioGRID

Citations: 4359

z-index 247.01

Short name BioGRID
Full name Biological General Repository for Interaction Datasets
Description BioGRID is an online interaction repository with data compiled through comprehensive curation efforts.
URL http://thebiogrid.org/
Year founded 2006
Last update & version 2017-02-01    v3.4.145
Availability Free to all users
University/Institution hosted University of Montreal
Address Montréal, Quebec H3C 3J7, Canada
City Mike Tyers
Province/State Quebec
Country/Region Canada
Contact name biogridadmin
Contact email biogridadmin@gmail.com
Data type(s)
Major organism(s)
Keyword(s)
  • protein and genetic interaction
  • translational modification
Publication(s)
  • The BioGRID interaction database: 2017 update. [PMID: 27980099]

    Andrew Chatr-Aryamontri, Rose Oughtred, Lorrie Boucher, Jennifer Rust, Christie Chang, Nadine K Kolas, Lara O'Donnell, Sara Oster, Chandra Theesfeld, Adnane Sellam, Chris Stark, Bobby-Joe Breitkreutz, Kara Dolinski, Mike Tyers
    Nucleic acids research 2017:45(D1)
    1 Citations (Google Scholar as of 2017-02-15)

    Abstract: 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. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  • The BioGRID interaction database: 2015 update. [PMID: 25428363]

    Andrew Chatr-Aryamontri, 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
    Nucleic acids research 2015:43(Database issue)
    333 Citations (Google Scholar as of 2017-02-15)

    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. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  • The BioGRID interaction database: 2013 update. [PMID: 23203989]

    Andrew Chatr-Aryamontri, Bobby-Joe Breitkreutz, Sven Heinicke, Lorrie Boucher, Andrew Winter, Chris Stark, Julie Nixon, Lindsay Ramage, Nadine Kolas, Lara O'Donnell, Teresa Reguly, Ashton Breitkreutz, Adnane Sellam, Daici Chen, Christie Chang, Jennifer Rust, Michael Livstone, Rose Oughtred, Kara Dolinski, Mike Tyers
    Nucleic acids research 2013:41(Database issue)
    545 Citations (Google Scholar as of 2017-02-15)

    Abstract: The Biological General Repository for Interaction Datasets (BioGRID: http//thebiogrid.org) is an open access archive of genetic and protein interactions that are curated from the primary biomedical literature for all major model organism species. As of September 2012, BioGRID houses more than 500 000 manually annotated interactions from more than 30 model organisms. BioGRID maintains complete curation coverage of the literature for the budding yeast Saccharomyces cerevisiae, the fission yeast Schizosaccharomyces pombe and the model plant Arabidopsis thaliana. A number of themed curation projects in areas of biomedical importance are also supported. BioGRID has established collaborations and/or shares data records for the annotation of interactions and phenotypes with most major model organism databases, including Saccharomyces Genome Database, PomBase, WormBase, FlyBase and The Arabidopsis Information Resource. BioGRID also actively engages with the text-mining community to benchmark and deploy automated tools to expedite curation workflows. BioGRID data are freely accessible through both a user-defined interactive interface and in batch downloads in a wide variety of formats, including PSI-MI2.5 and tab-delimited files. BioGRID records can also be interrogated and analyzed with a series of new bioinformatics tools, which include a post-translational modification viewer, a graphical viewer, a REST service and a Cytoscape plugin.

  • The BioGRID Interaction Database: 2011 update. [PMID: 21071413]

    Chris Stark, Bobby-Joe Breitkreutz, Andrew Chatr-Aryamontri, Lorrie Boucher, Rose Oughtred, Michael S Livstone, Julie Nixon, Kimberly Van Auken, Xiaodong Wang, Xiaoqi Shi, Teresa Reguly, Jennifer M Rust, Andrew Winter, Kara Dolinski, Mike Tyers
    Nucleic acids research 2011:39(Database issue)
    779 Citations (Google Scholar as of 2017-02-15)

    Abstract: The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans (http://www.thebiogrid.org). BioGRID currently holds 347,966 interactions (170,162 genetic, 177,804 protein) curated from both high-throughput data sets and individual focused studies, as derived from over 23,000 publications in the primary literature. Complete coverage of the entire literature is maintained for budding yeast (Saccharomyces cerevisiae), fission yeast (Schizosaccharomyces pombe) and thale cress (Arabidopsis thaliana), and efforts to expand curation across multiple metazoan species are underway. The BioGRID houses 48,831 human protein interactions that have been curated from 10,247 publications. Current curation drives are focused on particular areas of biology to enable insights into conserved networks and pathways that are relevant to human health. The BioGRID 3.0 web interface contains new search and display features that enable rapid queries across multiple data types and sources. An automated Interaction Management System (IMS) is used to prioritize, coordinate and track curation across international sites and projects. BioGRID provides interaction data to several model organism databases, resources such as Entrez-Gene and other interaction meta-databases. The entire BioGRID 3.0 data collection may be downloaded in multiple file formats, including PSI MI XML. Source code for BioGRID 3.0 is freely available without any restrictions.

  • The BioGRID Interaction Database: 2008 update. [PMID: 18000002]

    Bobby-Joe Breitkreutz, Chris Stark, Teresa Reguly, Lorrie Boucher, Ashton Breitkreutz, Michael Livstone, Rose Oughtred, Daniel H Lackner, Jürg Bähler, Valerie Wood, Kara Dolinski, Mike Tyers
    Nucleic acids research 2008:36(Database issue)
    647 Citations (Google Scholar as of 2017-02-15)

    Abstract: The Biological General Repository for Interaction Datasets (BioGRID) database (http://www.thebiogrid.org) was developed to house and distribute collections of protein and genetic interactions from major model organism species. BioGRID currently contains over 198 000 interactions from six different species, as derived from both high-throughput studies and conventional focused studies. Through comprehensive curation efforts, BioGRID now includes a virtually complete set of interactions reported to date in the primary literature for both the budding yeast Saccharomyces cerevisiae and the fission yeast Schizosaccharomyces pombe. A number of new features have been added to the BioGRID including an improved user interface to display interactions based on different attributes, a mirror site and a dedicated interaction management system to coordinate curation across different locations. The BioGRID provides interaction data with monthly updates to Saccharomyces Genome Database, Flybase and Entrez Gene. Source code for the BioGRID and the linked Osprey network visualization system is now freely available without restriction.

  • BioGRID: a general repository for interaction datasets. [PMID: 16381927]

    Chris Stark, Bobby-Joe Breitkreutz, Teresa Reguly, Lorrie Boucher, Ashton Breitkreutz, Mike Tyers
    Nucleic acids research 2006:34(Database issue)
    2054 Citations (Google Scholar as of 2017-02-15)

    Abstract: 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 >116 000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens. Over 30 000 interactions have recently been added from 5778 sources through exhaustive curation of the Saccharomyces cerevisiae primary literature. 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.

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Rate of accessibility:
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200 OK2017-06-27
200 OK2017-06-23
200 OK2017-06-20
200 OK2017-06-16
200 OK2017-06-13
200 OK2017-06-09
200 OK2017-06-06
200 OK2017-06-02
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200 OK2017-05-26
200 OK2017-05-23
200 OK2017-05-19
200 OK2017-05-16
200 OK2017-05-12
200 OK2017-05-09
200 OK2017-05-05
200 OK2017-05-02
200 OK2017-04-28
200 OK2017-04-25
200 OK2017-04-21
200 OK2017-04-18
200 OK2017-04-14
200 OK2017-04-11
200 OK2017-04-07
200 OK2017-04-04
200 OK2017-03-31
200 OK2017-03-28
200 OK2017-03-24
200 OK2017-03-21
200 OK2017-03-17
200 OK2017-03-14
200 OK2017-03-10
200 OK2017-03-07
200 OK2017-03-03
200 OK2017-02-28
200 OK2017-02-24
200 OK2017-02-21
200 OK2017-02-17
200 OK2017-02-14
200 OK2017-02-10
200 OK2017-02-07
200 OK2017-02-03
200 OK2017-01-31
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200 OK2017-01-24
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200 OK2017-01-10
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200 OK2016-12-02
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200 OK2016-10-14
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200 OK2016-10-07
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200 OK2016-07-29
200 OK2016-07-26
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200 OK2016-07-19
200 OK2016-07-15
200 OK2016-07-12
200 OK2016-07-08
200 OK2016-07-05
200 OK2016-07-01
200 OK2016-06-28
200 OK2016-06-24
200 OK2016-06-21
200 OK2016-06-17
200 OK2016-06-14
200 OK2016-06-10
200 OK2016-06-07
200 OK2016-06-03
200 OK2016-05-31
200 OK2016-05-27
200 OK2016-05-24
200 OK2016-05-20
200 OK2016-05-17
200 OK2016-05-13
200 OK2016-05-10
200 OK2016-05-06
200 OK2016-05-03
200 OK2016-04-29
200 OK2016-04-26
200 OK2016-04-22
200 OK2016-04-19
200 OK2016-04-15
200 OK2016-04-12
200 OK2016-04-08
200 OK2016-04-05
200 OK2016-04-01
200 OK2016-03-29
200 OK2016-03-28
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200 OK2016-03-21
200 OK2016-03-18
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200 OK2016-03-07
200 OK2016-03-04
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200 OK2016-02-19
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200 OK2016-02-15
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200 OK2016-02-08
200 OK2016-02-07
200 OK2016-02-05
200 OK2016-02-03
200 OK2016-02-01
200 OK2016-01-31
200 OK2016-01-29
200 OK2016-01-27
200 OK2016-01-25
200 OK2016-01-24
200 OK2016-01-22
200 OK2016-01-20
200 OK2016-01-18
200 OK2016-01-17
200 OK2016-01-15
200 OK2016-01-13
200 OK2016-01-11
200 OK2016-01-10
200 OK2016-01-08
200 OK2016-01-06
200 OK2016-01-04

Tags

Interaction and Network Modification Protein
protein and genetic interaction translational modification

Record metadata

  • Created on: 2015-06-20
  • Curated by:
    • Shixiang Sun [2017-02-15]
    • Zhang Zhang [2016-04-26]
    • Mengwei Li [2016-03-31]
    • Mengwei Li [2016-03-29]
    • Mengwei Li [2015-11-29]
    • Mengwei Li [2015-06-26]
Stats