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En kunnskapsgraftilnærming for å belyse rollen som organellære veier i sykdom via biomedisinske rapporter
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
En beregningsprotokoll, CaseOLAP LIFT, og et brukstilfelle presenteres for å undersøke mitokondrielle proteiner og deres assosiasjoner med kardiovaskulær sykdom som beskrevet i biomedisinske rapporter. Denne protokollen kan enkelt tilpasses for å studere brukervalgte cellulære komponenter og sykdommer.
