DGIdb - Mining the druggable genome

By Malachi Griffith, Obi L. Griffith, Adam C. Coffman, James V. Weible, Joshua F. McMichael, N. Spies, J. Koval, Indraniel Das, Matthew B. Callaway, James M. Eldred and 13 more. Nature Methods, 2013

505 citations recorded by the source corpus.

The Drug-Gene Interaction database (DGIdb) mines existing resources that generate hypotheses about how mutated genes might be targeted therapeutically or prioritized for drug development. It provides an interface for searching lists of genes against a compendium of drug-gene interactions and potentially 'druggable' genes. DGIdb can be accessed at http://dgidb.org/.

Subfields: Computational Theory and Mathematics, Molecular Biology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/8d55fbdb8429b720a4fb0004b87f9594ba9584ff

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Citations in the corpus

Integration of the Drug–Gene Interaction Database (DGIdb 4.0) with open crowdsource efforts (2020, background): “Originally released in 2013, the Drug–Gene Interaction database (DGIdb) (1) serves as a central aggregator of information on drug-gene interactions and druggability from multiple diverse sources.”
Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources (2020, background): “The Drug-Gene Interaction Database (DGIdb) is an NLP-curated database that stores information about mutated genes that could be useful to identify targets for drug development [273].”
The BioGRID interaction database: 2017 update (2016, background): “…of the major specialized chemical interaction databases, including DrugBank (37), HMdb (61), T3DB (62), BindingDB (63), CTD (64), Therapeutic Target DB (65), ChemBank (66), PharmGKB (67), DGIdb (68), Pub-Chem (69) and ChEMBL (70) to determine the shared fields housed in each of these databases.”
DGIdb 3.0: a redesign and expansion of the drug–gene interaction database (2017, unknown): “org) was first released in 2013 to consolidate drug–gene interactions and potentially druggable genes into a single resource with a powerful interface to query these data (1).”
DGIdb 2.0: mining clinically relevant drug–gene interactions (2015, background): “The drug search results work in much the same way as the gene search results (21).”
A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia (2016, background): “(D) Drug Gene Interaction database (DGIdb) (Griffith et al., 2013) categorization of AML-specific cell-essential genes into ‘‘druggable’’ categories defined by the DGIdb.”
Machine learning approaches and databases for prediction of drug–target interaction: a survey paper (2020, background): “The first release (in 2013) of DGIdb integrated 13 data sources that cover information in disease-related human genes, drugs, drug interactions and potential druggability [263,264].”
SpeedSeq: Ultra-fast personal genome analysis and interpretation (2014, methodology): “Two new have been added to GEMINI: the COS-MIC catalogue of somatic mutations in cancer[31] and DGIdb, the Drug-Gene Interaction database[33].”
SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution (2014, background): “As an example, the Drug-Gene Interaction Database [57] identifies three genes in the AML sample as as potentially druggable: (DRD2, KCNQ2, and P2RY2).”