Protein Structure Prediction: Harnessing AlphaFold/ColabFold

Course Description

AlphaFold represents a dramatic increase in the power of AI systems to predict a protein’s 3D structure from its amino acid sequence. This nanocourse will introduce how predictive models like Alphafold/Collab work, their strengths and limitations, and how to interpret their predictive results.

This is a hands-on workshop; participants will use Alphafold and ColabFold, submit computing jobs to the O2 computing platform, and visualize 3D structures. No prior computational experience is required – the workshop will introduce participants to machine learning and the command-line environment.

Instructors: Ogie Avramovska, Curriculum Fellow in Genetics and Genomics, and Chris Magnano, Curriculum Fellow in the Center for Computational Biomedicine
Guest Lecturer: Sergey Ovchinnikov (John Harvard Distinguished Science Fellow)
Technical Support: Alex Truong and Calvin Cox (Research Computing)
Milestone Criteria: Attendance at all 3 sessions and in-class submission of nanocourse reflection in session 3

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SESSION 1 - Wednesday, March 22nd, 3:30 - 5:30, TMEC 250 
(Limited to 50)

SESSION 2 - Monday, March 27th, 3:30 - 5:30, TMEC 333
(Limited to 24 - Hands-on Session)

SESSION 3 - Wednesday, March 29th, 3:30 - 5:30, TMEC 338
(Limited to 24 - Hands-on Session)