Explore a 29-minute talk on leveraging deep learning and knowledge graphs for drug repurposing. Learn how to accelerate the discovery of new treatments by finding novel uses for existing drugs. Dive into the process of unifying structured and unstructured data sets into a knowledge graph, and discover techniques for predicting latent relationships. Cover the essential steps of building a knowledge graph, predicting latent relationships, and applying these insights to repurpose existing drugs. Gain valuable insights into data sources, graph building, relationship extraction, and various modeling approaches. Understand how this innovative approach can significantly reduce the time and cost associated with traditional drug discovery methods.
Overview
Syllabus
Introduction
What is drug repurposing
How Vicecube helped
Data sources
Four steps
Data sets
Drkg
Unifying Data
Linking Data
Link Prediction
Graph Building
Graph Relationships
Explicit Relationships
Relationship Extraction
Types of Models
Method
Next steps
Conclusion
Taught by
Databricks
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