How deep can we decipher protein evolution with deep learning models

Övrig text i vetenskaplig tidskrift, 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.