opentargets-database

To retrieve target-disease associations for drug discovery, query the Open Targets Platform GraphQL API to fetch multi-modal genetic evidence, including GWAS studies, QTL credible sets, and L2G predictions. The skill automates pagination and retry logic for efficient data extraction.

Ranking genes associated with a specific disease using GWAS evidence requires querying Locus-to-Gene (L2G) scores and filtering by credible sets. This skill retrieves the necessary genetic data to prioritize the most likely causal genes for therapeutic research.

Automated pagination handles large biological datasets by systematically fetching sequential data pages from the bioinformatics API. This skill implements pagination alongside retry logic and response truncation to ensure safe, efficient handling of complex multi-modal biological data.

You can assess druggability and clinical trial safety for therapeutic targets by retrieving specific tractability information through the GraphQL API. This skill aggregates the multi-modal evidence needed to evaluate target identification and safety profiles.

You need a specific disease identifier format, such as the EFO ID like EFO_0000685, to fetch pharmacology and genetics data. The skill uses these identifiers to accurately query and save associated biological data from the platform.

Response truncation occurs during complex biological data retrieval to ensure efficient and safe data handling when query results exceed size limits. This mechanism prevents API timeouts and failures while fetching large GWAS studies and QTL credible sets.