BioGRID

Background BioGRID (Biological General Repository for Interaction Datasets) is a community-focused biomedical database that compiles experimentally validated molecular interactions from the primary literature. Its scope includes protein–protein interactions, genetic interactions, chemical associations, post‑translational modifications (PTMs) and curated genome‑scale CRISPR screen results. Data are collected through comprehensive manual curation and organized into a versioned index covering major model organisms and human studies, with themed curation projects and specialized datasets addressing disease‑relevant topics. Core capabilities BioGRID provides a searchable index and bulk downloads in multiple standardized formats so users can integrate curated interaction data into their own analyses and pipelines. Each record is annotated with structured metadata captured during curation — for example experimental system, phenotype, cell line, evidence type and citation — enabling filtering and programmatic use. The BioGRID Open Repository of CRISPR Screens (ORCS) is a dedicated component that aggregates genome‑wide CRISPR screen results from the literature; ORCS entries are fully searchable by gene/protein, phenotype, cell line, authors and other attributes and are accompanied by detailed CRISPR experimental metadata. Regular curation updates keep datasets current (themed projects updated monthly; ORCS updated quarterly), and a public presence (including a GitHub organization) supports transparency and community engagement. Example use cases Researchers use BioGRID to build and validate interaction networks, prioritize candidate genes or targets, and interpret high‑throughput experiments. Typical workflows include: (1) assembling an evidence‑backed interaction neighborhood for a protein of interest to generate mechanistic hypotheses; (2) cross‑referencing CRISPR screen hits against known genetic or chemical interactions to nominate synthetic lethal partners or druggable nodes; (3) extracting PTM and chemical association data to explain regulatory changes or guide follow‑up experiments; and (4) leveraging themed curation projects (e.g., Alzheimer’s disease, autophagy, Fanconi anemia, glioblastoma, HPV, yeast kinome, COVID‑19 viral–host interaction curation, and synthetic protein interaction annotations) to focus analyses on curated, disease‑relevant subsets of the literature. Because entries include rich provenance and experimental detail, BioGRID is also commonly used to build training sets for computational methods and to validate predicted interactions. Access, tools and integrations All BioGRID data are accessible via the project’s web search index and as downloadable files in standard, machine‑readable formats. The site emphasizes structured metadata and versioning so users can reproduce analyses against specific releases. Utility tools and integrations include a browser extension (GIX) that lets users retrieve gene product information directly from any webpage by double‑clicking gene names or accessions, and the ORCS portal for CRISPR screen exploration. BioGRID’s publicly visible code and resources (including a GitHub presence) make it straightforward to automate data retrieval or integrate BioGRID exports into bioinformatics pipelines and network analysis tools. For domain‑focused projects, themed curation pages and project contact points allow researchers to suggest genes, contribute expertise, or request custom curation efforts. In summary, BioGRID is a mature, literature‑driven interaction repository geared toward enabling reproducible network biology and experimental follow‑up. Its combination of manual curation, structured metadata, disease‑focused projects and CRISPR screen aggregation makes it a practical resource for wet‑lab scientists, computational biologists and translational researchers seeking curated, provenance‑rich interaction data.