primekg

You can query a biomedical knowledge graph using the get_disease_context function to retrieve direct gene and drug associations for a specific disease from a local PrimeKG CSV dataset.

PrimeKG is a curated knowledge graph consolidating multiscale biological data across genes, drugs, diseases, and phenotypes from over 20 primary databases to support network pharmacology and hypothesis generation.

Yes, you can use pandas alongside the search_nodes and get_neighbors Python functions to find specific entities by name and type, and retrieve their direct neighbors with supporting evidence from the local knowledge graph dataset.

Yes, PrimeKG requires a local CSV dataset to operate. The Python functions search_nodes, get_neighbors, and get_disease_context process this local file to analyze disease context and explore drug-disease paths for hypothesis generation.

The best way to explore network pharmacology relationships is using PrimeKG, which consolidates data from 20+ primary databases into a single knowledge graph. You can retrieve direct neighbors and analyze local disease context to generate hypotheses.

Querying multiscale biological data from a local PrimeKG dataset is limited by the scope of its 20+ integrated primary databases. Analysis is restricted to the nodes, direct neighbors, and disease context available within the local CSV file.