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Protein design roundtable discussion: real challenges and practical solutions
00:23:55
AI driven protein design workflow: A practical example
00:21:12
Modern Protein Docking: Traditional Methods vs AI Tools
00:24:21
Protein design compute explained: when to use GPU vs CPU
00:19:25
Cutting-edge ML tools for protein design pipelines
00:33:32
Inverse folding using ProteinMPNN
00:29:56
Backbone generation in protein design workflows
00:22:25
AlphaFold3 Structure Prediction: what's new and why it matters
00:24:46
PyTorch explained: from neural networks to real-world models
00:33:10
ESM Fold Structure Prediction
00:16:20
AlphaFold2 Structure Prediction
00:45:48
Protein structure prediction: history, challenges, and AI breakthroughs
00:10:42
Tools intro: PyMOL & VS Code
00:13:49
How to create software that others want to use
00:41:46
Adding Code to Rosetta
00:35:22
SimpleMetric Subclassing: integrating metrics into RosettaScripts
00:11:08
Rosetta development guide: resources, coding conventions, and best practices
00:55:18
Loop modeling workflows in Rosetta
00:07:32
Controlling flexibility in Rosetta
00:36:28
Shell scripting essentials for large-scale data processing
00:26:51
Rosetta Library Structure 4
00:35:51
RosettaScripts Mover subclassing: Building your first mover class
00:22:57
More C++ classes: this pointer, const, and function signatures
00:47:41
RosettaScripts in action: designing your first workflow
00:13:53
RosettaScripts explained: building custom protocols in Rosetta
00:34:56
Fold trees explained: how protein structure are modeled in Rosetta
00:36:53
Rosetta library structure 3
00:35:18
Unit testing in Rosetta: how to know your code works
00:25:10
Rosetta Library Structure 2
00:35:52
Rosetta Library Structure 1
00:33:28