Research

The Biomedical Knowledge Graph Research Center dedicates itself to advancing the construction and application of knowledge graphs (KGs) in biomedicine, fostering intelligent progress in medical research and clinical practice through structured knowledge frameworks. By systematically integrating multi-source heterogeneous biomedical data, the team pioneers key technologies in knowledge extraction, fusion, embedding, and reasoning, and constructs domain-specific KGs spanning disease mechanisms, clinical diagnosis, and drug discovery. Core achievements include specialized platforms for disease-specific KG development and multimodal knowledge reasoning systems, delivering modular solutions for target prediction, personalized treatment, and other scientific and clinical applications.

Anchored by National Key Research and Development Program of China, "Precision Medicine Knowledge Base Construction for Disease Research (2016YFC0901900)", the center has established Precision Medicine knowledgebase application platform (PMapp), the nation's first independently developed precision medicine knowledge platform. Integrating over 60 authoritative biomedical databases, PMapp features a precision medicine knowledge graph comprising 50 million triples, breaking the long-term monopoly of Western counterparts in knowledge infrastructure. Milestone accomplishments include: systematic construction of knowledge graphs for 11 major diseases (Bioinformatics 2022) and 115 rare diseases (Comput Biol Med 2023); development of multimodal graph reasoning techniques for drug repositioning in rare diseases; and creation of predictive models such as MDTips for drug-target interaction analysis (Bioinformatics 2023) and TransCDR for multi-omics drug response profiling (BMC Biology 2024).