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Un approccio basato su Knowledge Graph per chiarire il ruolo delle vie organellari nella malattia attraverso referti biomedici
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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
Capitoli
- 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
Vengono presentati un protocollo computazionale, CaseOLAP LIFT, e un caso d'uso per studiare le proteine mitocondriali e le loro associazioni con le malattie cardiovascolari come descritto nei rapporti biomedici. Questo protocollo può essere facilmente adattato per studiare i componenti cellulari e le malattie selezionate dall'utente.
