Figure 2. Example of a sub-graph constructed from the QIAGEN biomedical knowledge graph. In this knowledge graph representation, gene and gene product entities are aggregated at the ortholog ...

Cedars-Sinai scientists unveil a powerful agentic AI model, ESCARGOT, that harnesses multiple intelligent agents and biomedical knowledge graphs to deliver sharper, faster, and more reliable ...

Every Cure is building a biomedical knowledge graph, which documents known relationships between biomedical concepts such as drugs, genes, proteins, cell types, tissue types and organ systems. The ...

Causaly today announced new scientific AI agents that provide research teams with the industry's most comprehensive biomedical knowledge for drug discovery. With agentic AI in Causaly Discover ...

We have developed and tested an integrated graph database, BioMedical Evidence Graph, that connects patient sample data, cell-line drug-response data, and multiple knowledge bases. Simple queries to ...

Knowledge graph-based recommender systems are able to help solve these challenges to an extent. In this approach, user and item entities are connected through multiple relationships.

Ro5’s platform leverages a proprietary Biomedical Knowledge Graph, comprising over 85 million nodes and approximately 400 million relationships, to uncover novel associations in biological ...

Ro5’s platform utilises a biomedical knowledge graph containing more than 85 million nodes and 400m relationships to find new connections in biological processes and enable evaluation of drug ...