Machine learning-aided engineering of hydrolases for PET depolymerization

By Hongyuan Lu, D. Diaz, Natalie J. Czarnecki, Congzhi Zhu, Wantae Kim, Raghav Shroff, Daniel J. Acosta, Brad Alexander, Hannah O. Cole, Yan Zhang and 3 more. Nature, 2022

917 citations recorded by the source corpus.

Subfields: Biomaterials, Genetics, Pollution

View Paper: https://www.semanticscholar.org/paper/8fedd23c1604dfeed02b75f8d38c1d7e33beee3a

How researchers see this paper

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1. Noelia Ferruz
2. Steffen Schmidt
3. Birte Höcker
4. Brian L. Trippe

Citations in the corpus

• ProtGPT2 is a deep unsupervised language model for protein design (2022, background): “Since protein design has an enormous potential to solve problems in fi elds ranging from biomedical to environmental sciences 25,26 , we believe that ProtGPT2 is a timely advance towards ef fi cient high-throughput protein engineering and design.”