The BioGRID interaction database: 2017 update

By A. Chatr-aryamontri, Rose Oughtred, Lorrie Boucher, J. Rust, Christie S. Chang, Nadine Kolas, Lara O'Donnell, S. Oster, Chandra L. Theesfeld, Adnane Sellam and 4 more. Nucleic Acids Res., 2016

903 citations recorded by the source corpus.

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.

Subfields: Computational Theory and Mathematics, Molecular Biology, Pharmacology

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Citations in the corpus

Next-Generation Machine Learning for Biological Networks. (2018, positive): “As an example application, one could use existing network knowledge from sources such as BioGRID (Chatr-Aryamontri et al., 2017; Stark et al., 2006)—a database of gene interactions, protein-protein interactions, chemical interactions and post-translational Cell 173, June 14, 2018 1585 Figure 2.”
Mut2Vec: distributed representation of cancerous mutations (2018, methodology): “Furthermore, we added structured biological knowledge using the PPI network BioGRID [17].”
AnimalTFDB 3.0: a comprehensive resource for annotation and prediction of animal transcription factors (2018, methodology): “We got PPI data for 19 species from BioGRID (28) and human PPI data from HPRD (29).”
The BioGRID interaction database: 2019 update (2018, background): “Since the previous update (23), a new resource within BioGRID called the Open Repository for CRISPR Screens (ORCS) has been developed to house and distribute large-scale CRISPR screen datasets across multiple model organism species (see https: //orcs.”
WebGestalt 2017: a more comprehensive, powerful, flexible and interactive gene set enrichment analysis toolkit (2017, methodology): “As another example, compared to the 1993 protein interaction modules from human and mouse in the previous version, the new version includes 2979 modules derived from the protein–protein interaction networks of 11 organisms downloaded from BioGRID (9).”
The Comparative Toxicogenomics Database: update 2019 (2018, background): “External integration of CTD content with annotations from Gene Ontology (29), KEGG (30), Reactome (31) and BioGRID (32) produces an additional 9.4 million inferences (Table 1).”
Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics (2019, background): “The confidence level of an experimentally observed regulation can be tentatively measured by the number of published experimental sources of evidence (46,47).”
Hierarchical cooperation of transcription factors from integration analysis of DNA sequences, ChIP-Seq and ChIA-PET data (2019, methodology): “We also build the reference PPI on the basis of STRING [49] and BioGRID [50].”