About this Event
Understanding the three-dimensional structure of a protein is often key to understanding its function, yet experimentally determining structures is time-consuming and resource intensive. Recent advances in deep learning have made accurate computational structure prediction possible, transforming this area of biological research. This workshop will introduce AlphaFold (versions 2 and 3), a deep-learning model that predicts protein structure from amino acid sequences. Participants will learn how to run AlphaFold to generate structure predictions on Quest. We will cover preparing input sequences, submitting jobs with appropriate GPU resources, and interpreting confidence metrics such as pLDDT, PAE, and pTM scores.
This workshop requires a laptop with a terminal application installed and expects familiarity with working from the command line or attendance at the ‘Working from the Command Line’ workshop.
Event venue & nearby stays
Wieboldt Hall, 339 East Chicago Avenue, Chicago, United States
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