How deep can we decipher protein evolution with deep learning models
Other text in scientific journal, 2024

Evolutionary-based machine learning models have emerged as a fascinating approach to mapping the landscape for protein evolution. Lian et al. demonstrated that evolution-based deep generative models, specifically variational autoencoders, can organize SH3 homologs in a hierarchical latent space, effectively distinguishing the specific Sho1(SH3) domains.

Author

Xiaozhi Fu

Chalmers, Life Sciences, Systems and Synthetic Biology

PATTERNS

2666-3899 (ISSN)

Vol. 5 8 101043

Subject Categories

Biological Sciences

DOI

10.1016/j.patter.2024.101043

More information

Latest update

10/11/2024