Watch a 22-minute symposium talk from the Machine Learning in Drug Discovery series where Associate Professor Jian Tang from Mila-Quebec AI Institute and HEC Montreal explores geometric deep learning approaches for protein understanding and design. Delve into cutting-edge artificial intelligence applications in protein science, focusing on how geometric deep learning techniques can be leveraged to better comprehend protein structures and facilitate innovative protein design strategies. Learn about the intersection of machine learning and drug discovery through this presentation delivered at the Broad Institute's specialized symposium.
Geometric Deep Learning for Protein Understanding and Design
Overview
Syllabus
Machine Learning in Drug Discovery Symposium - Jian Tang
Taught by
Broad Institute
Related Courses
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Geometric Deep Learning for Protein Understanding
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Machine Learning for Protein Engineering in Drug Discovery
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Programmable Generative Protein Design - Machine Learning in Drug Discovery
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PROTPARDELLE: An All-Atom Protein Generative Model - Broad Institute Machine Learning in Drug Discovery Symposium 2023
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Geometric Deep Learning for Drug Discovery
5.0 -
Computer-Aided Drug Design
