Machine learning for proteins

Title Description
Machine learning for protein engineering seminar series A virtual seminar series covering recent work in machine learning for protein engineering.
Protein sequence models Code and pretrained models for proteins.
ESM Excellent codebase from Meta with several pretrained protein models.
FLIP Benchmarks for ML on protein fitness landscapes.
Adaptive machine learning for protein engineering A review covering how to use machine learning to choose protein sequences to characterize.
Protein sequence design with deep generative models A review covering VAEs, GANs, and language models on protein sequences.
Machine learning-guided directed evolution for protein engineering) A review covering ML for protein engineering, including an overview of methods, two case studies, and future outlook.
Papers on machine learning for proteins A github repository listing papers on machine learning for proteins.

General statistics and machine learning

Title Description
Distribution explorer A tool to explore commonly-used probability distributions, including information about the stories behind them.
Gaussian processes for machine learning Textbook on Gaussian processes.
Beta and Alpha Michael Betancourt’s many excellent tutorials on probabilistic computing and Bayesian statistics.
Visual exploration of GPs A visual tutorial on GPs that provides good intuition for their behavior.

I also really like Sam Finlayson’s list of ML resources.