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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
This content is Free Access.
1Department of Physiology,UCLA School of Medicine, 2Scalable Analytics Institute (ScAi) at Department of Computer Science,UCLA School of Engineering, 3NIH BRIDGE2AI Center at UCLA & NHLBI Integrated Cardiovascular Data Science Training Program,UCLA, 4Medical Informatics,University of California at Los Angeles (UCLA), 5Department of Medicine (Cardiology),UCLA School of Medicine
Chapters
- 00:04Introduction
- 01:09Running the Docker Container
- 01:53Preparing the Diseases and Proteins
- 03:16Analyzing the Results
- 04:20Predictive Analysis
- 05:40Results: Top Protein‐Disease and Pathway‐Disease Associations and Application of Deep Learning for Knowledge Graph Completion
- 06:40Conclusion
A computational protocol, CaseOLAP LIFT, and a use case are presented for investigating mitochondrial proteins and their associations with cardiovascular disease as described in biomedical reports. This protocol can be easily adapted to study user-selected cellular components and diseases.
