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Updated: Mar 24, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
Published on: October 13, 2023
Desiderata for a biomedical knowledge network: opportunities, challenges and future directions.
Chunlei Wu1, Hongfang Liu2, Jason Flannick3
1Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
Biomedical knowledge graphs (KGs) require domain-specific reasoning, standardized data, and robust validation for effective AI-driven discovery. Addressing these challenges will advance the biomedical knowledge network and its applications.
Area of Science:
- Biomedical informatics
- Knowledge representation and reasoning
- Computational biology
Background:
- Knowledge graphs (KGs) are crucial for knowledge discovery in complex biomedical data.
- Biomedical KGs need to support dynamic reasoning and abstraction over large, evolving datasets.
- Establishing standards, preserving provenance, and enforcing policies are critical for actionable discovery.
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