Protein ML Talks

Recent talks applying the latest protein-ML models for design under the framework of p(sequence, structure, function).

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Author's profile picture Tianyu Lu on Talks, Protein, and ML

Protein ML Colab Notebooks

Seven Google Colab notebooks made for the CSBERG Synthetic Biology course. Content delivered in Summer 2021.

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Author's profile picture Tianyu Lu on Education, Protein, and ML

NeuralODE for Gene Network Design

Colab notebook for designing gene regulatory networks by specifying desired dynamics then backproping through an ODE solver.

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Author's profile picture Tianyu Lu on Research, Dynamics, and ML

Potts Model Visualized

Inspired by The Illustrated Transformer, this post unpacks the symbols behind a Potts Model and visualizes how its parameters help us understand the evolution of protein sequence and structure.

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Author's profile picture Tianyu Lu on Communication, Protein, and ML

Generative Enzymes Model

Adapting the CbAS algorithm to generate plastic degrading enzymes with information from structure.

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Author's profile picture Tianyu Lu on Research, Protein, and ML

Protein Structure Design

Lab meeting slides at Philip Kim’s group on classical and machine learning guided protein design, with a walkthrough of how to use MaSIF to search for DNA mimicking proteins in the PDB.

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Author's profile picture Tianyu Lu on Research, Protein, and ML

Protein Design Lectures

The lectures on protein design below are part of a summer workshop series on synthetic biology organized by he Canadian Synthetic Biology Education Research Group CSBERG.

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Author's profile picture Tianyu Lu on Teaching, Protein, and ML

Optimizing Plastic Degrading Proteins

We present a generalizable and automated pipeline for protein design. Our model can be applied to the optimization of any protein class, even those with scarce data.

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Author's profile picture Tianyu Lu on iGEM, Protein, and ML