primekg

To query a precision medicine knowledge graph for biological data, you can search for specific genes, drugs, diseases, and phenotypes. The Skill retrieves associated entities and clinical evidence to provide neighbors and context for the requested nodes.

The best way to find drug-disease paths for drug repurposing is to query the knowledge graph to identify potential connections. This Skill discovers paths between drugs and diseases to highlight repurposing opportunities using network pharmacology.

To retrieve associated genes and phenotypes for a specific disease, you query the knowledge graph to analyze disease context. This Skill summarizes associations by returning related genes, drugs, and phenotypes for the given disease node.

Yes, you can use pandas for network pharmacology data manipulation because pandas is a required dependency. You need Python and pandas installed to handle the biological data structures and perform the data manipulation required for querying.

PrimeKG supports searching for drugs and phenotypes within the same knowledge graph structure. You can search across genes, proteins, drugs, diseases, and phenotypes to retrieve associated entities and clinical evidence for comprehensive analysis.

A limitation of using this knowledge graph for drug discovery queries is that it requires Python and pandas to process the data. Results depend on the existing biological data connections within PrimeKG, and complex queries may require additional data manipulation outside the Skill.