CBKH: The Cornell Biomedical Knowledge Hub

The rapidly increasing biomedical knowledge, derived from biological experiments or gained from clinical practice, has become the important treasure in the biomedical research. The emerging knowledge graphs (KGs) provide an efficient and effective way to organize and retrieval the huge and increasing volume of biomedical knowledge. A biomedical KG (BKG) typically stores and represents knowledge by constructing a semantic network describing entities and the relationships between them. Previous efforts have been conducted to construct and curate BKGs by comprehensively integrating various biomedical data resources. Though the resulting BKGs have made a significant progress in this filed in advancing biological and medical research, there remain a big gap to a perfect one that is comprehensive and fine-grained enough. To this end, in the present study, we collected and integrated data from diverse well-curated biomedical knowledge bases and BKGs to curate a more comprehensive one, named the Cornell Biomedical Knowledge Hub (CBKH). To enhance the usage in accelerating biomedical research, we deployed CBKH using the famous graph database, Neo4j. This is a continuing effort and we are adding in more and more contents in CBKH to support the various complex needs in biomedical data analysis. Please contact us if you have better ideas and suggestions.