How deep can we decipher protein evolution with deep learning models
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Publisher
Elsevier BV
Reference10 articles.
1. Machine learning for evolutionary-based and physics-inspired protein design: Current and future synergies;Malbranke;Curr. Opin. Struct. Biol.,2023
2. Learning the protein language: Evolution, structure, and function;Bepler;Cell Syst.,2021
3. Clustering predicted structures at the scale of the known protein universe;Barrio-Hernandez;Nature,2023
4. Deciphering protein evolution and fitness landscapes with latent space models;Ding;Nat. Commun.,2019
5. Latent generative landscapes as maps of functional diversity in protein sequence space;Ziegler;Nat. Commun.,2023
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