QIAGEN OmicSoft and Biomedical Knowledge Base
Supercharge your AI in drug discovery with high-quality biomedical data
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Jesper Ryge (Idorsia Pharmaceuticals), Alex Jarasch (Neo4j) and Venkatesh Moktali (QIAGEN Digital Insights) come together to showcase the practical applications of high-quality biomedical relationships data from the QIAGEN Biomedical Knowledge Base (BKB) to accelerate, improve and transform research in drug discovery and pharmaceutical development. By applying AI to a gene-disease knowledge graph, they identify promising drug targets and key mechanisms underlying diseases. A brief introduction to Neo4j shows how graph-centric analysis and visualizations facilitate the effective exploration of large knowledge graphs like BKB. This integration of high-quality curated data, AI-driven analysis and advanced visualization provides valuable insights and accelerates the progress of precision medicine.
In this webinar, you’ll learn how you can:
Build disease interactomes using protein-protein interactions
Identify high-quality drug targets using inferred causal interactions
Choose targets with the least likelihood of adverse outcomes by leveraging the depth of the data in BKB
Formulate plausible hypotheses using state-of-the-art graph visualization
Don’t miss this chance to learn how to supercharge your AI toolbox to transform your drug discovery.
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