Biomedical Knowledge Graph

Biomedical knowledge graphs (BioKGs) are structured representations of biomedical data, aiming to integrate diverse information sources for improved knowledge discovery and application. Current research focuses on enhancing BioKG construction and analysis through advanced techniques like graph neural networks (e.g., message-passing models), contrastive learning for improved term representation and clustering, and the integration of large language models (LLMs) to leverage unstructured text data. These advancements are improving tasks such as link prediction, treatment effect estimation, and drug discovery, ultimately accelerating biomedical research and potentially leading to more effective healthcare solutions. The development of comprehensive, easily updatable BioKGs, like Know2BIO, is also a key area of focus.