Machine Learning For Enzyme Engineering
Machine Learning for Enzyme Engineering is a computational methodology that integrates machine learning algorithms with biochemical data to predict and optimize enzyme functions, distinguishing itself by enabling data-driven design and directed evolution of enzymes with enhanced catalytic properties, specificity, or stability.
77
Publications
4.8K
Citations
422
Authors
187
Institutions
Publications per year
2017–2026
56
Parents
77
Machine learning-aided engineering of hydrolases for PET depolymerization
Hongyuan Lu, Daniel J. Diaz, Natalie J. Czarnecki et al. · Nature · 2022 · 1.2K citations
Machine Learning in Enzyme Engineering
Stanislav Mazurenko, Zbyněk Prokop · ACS Catalysis · 2019 · 420 citations · Full text
Machine Learning on a Robotic Platform for the Design of Polymer–Protein Hybrids
Matthew Tamasi, Roshan Patel, Carlos H. Borca et al. · Advanced Materials · 2022 · 177 citations · Full text
1–5 of 77
422
5
h-index
5
h-index
3
h-index
3
h-index
3
h-index
1–5 of 422
187

Chinese Academy of Sciences
Beijing, China
6 h-index
11 publications
467 citations
Universität Greifswald
Greifswald, Germany
5 h-index
17 publications
809 citations
Universiti Putra Malaysia
Seri Kembangan, Malaysia
5 h-index
23 publications
885 citations
University of Chinese Academy of Sciences
Beijing, China
4 h-index
5 publications
243 citations
Beijing National Laboratory for Molecular Sciences
Beijing, China
3 h-index
3 publications
125 citations
Chinese Academy of Agricultural Sciences
Beijing, China
3 h-index
15 publications
550 citations
The University of Texas at Austin
Austin, United States
3 h-index
38 publications
15.8K citations
Institute of Chemistry
Beijing, China
3 h-index
3 publications
125 citations
1–8 of 187
7 publications · 540 citations
7
h-index
CBAC · 5 publications · 184 citations
5
h-index
5 publications · 199 citations
5
h-index
Repository · 3 publications · 67 citations
3
h-index
2 publications · 37 citations
2
h-index
1–5