University of Wisconsin–Madison

Tag: AlphaFold2

Nobel-Winning AlphaFold2 and RosettaFold: Cracking the Protein Folding Mystery

Summary “Explore how David Baker, Demis Hassabis, and John Jumper won the 2024 Nobel Prize in Chemistry for their advances in computer-assisted protein design.” Video: How AI Cracked the Protein Folding Code and Won a Nobel Prize This 22min19 video provides a very good explanation of the origins of the research in protein structure, from …

AlphaFold2 with ColabFold in Container

Summary Run the ColabFold version of AlphaFold2 on your laptop (slow without GPU) or on a large Linux cluster. The full tutorial with scripts is located at ColabFold with HTCondor What is AlphaFold2 Excerpt from a previous post (Five ways to run AlphaFold) AlphaFold can accurately predict 3D models of protein structures by providing an …

AlphaFold2 with full databases and multimer option

Summary This article describes running AlphaFold2 with full databases at the UW-Madison Center for High Throughput Computing (CHTC) and is part of an article series titled Five ways to run AlphaFold. CHTC cluster, HTCondor, Containerization The UW-Madison Center for High Throughput Computing (CHTC) offers free computing accounts for all UW-Madison personnel and offer the full …

AlphaFold code

DeepMind and Google have created a method to access the code on GitHub. All the details to install AlphaFold locally are on the "readme" page, visible on the lower portion of the GitHub page ColabFold (See my Blog: Google colab is a free cloud notebook environment).

AlphaFold background

Predicting protein three-dimensional (3D) structures given a linear sequence of amino acids. The AlphaFold2 breakthrough.