Explore a recorded session from the 2024 Machine Learning for Drug Discovery Summer School hosted at Mila, focusing on binding affinity prediction using machine learning-based docking techniques. Learn from speakers Stephan Thaler and Cristian Gabellini as they delve into the intricacies of Lab 2, which covers the explanation of ML-based docking for predicting binding affinities. Gain valuable insights into this cutting-edge approach in drug discovery over the course of 26 minutes. For those interested in connecting with the speakers and accessing additional resources, visit the Valence Labs portal at https://portal.valencelabs.com/.
Overview
Syllabus
Lab 2 - Binding Affinity Prediction with ML Based Docking Explanation
Taught by
Valence Labs
Related Courses
-
Binding Affinity Prediction with Machine Learning-Based Docking - Lab 2
-
Machine Learning in Structure-Based Drug Discovery - Day 2
-
Virtual Screening Explanation - Lab 1
-
Leveraging Molecular ML and Property Prediction in Drug Design
-
Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design
-
Target Deconvolution Explanation - Lab 4
