Contribute to evolutionaryscale/esm development by creating an account on GitHub.

Many proteins’ biological functions rely on interconversions between multiple conformations occurring at micro-to millisecond (µs-ms) timescales. A lack of standardized, large-scale experimental data ...

Advances in metagenomics, deep learning, and generative protein design have enabled broad in silico exploration of sequence space, but experimental characterization is still constrained by the cost an...

ML-guided enzyme engineering. Contribute to google-deepmind/nuclease_design development by creating an account on GitHub.

YouTube video by ML for protein engineering seminar series

Thomas et al. introduce TeleProt, a framework for guiding protein library design with machine learning, and validate it in an enzyme engineering campaign to optimize the endonuclease NucB. Across 4 ro...

Amino acid substitution rate matrices are fundamental to statistical phylogenetics and evolutionary biology. Estimating them typically requires reconstructed trees for massive amounts of aligned...