An evolution-based model for designing chorismate mutase enzymes is a research paper published in Science (2020). On theSindex it has a DataRank of 0. It has been cited 365 times.
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National Institutes of Health
Grant: GM12345
Welch Foundation
Grant: I-1366
European Commission Directorate-General for Research and Innovation
Grant: 734439
Agence Nationale de la Recherche
Grant: CE30-0021-01
Swiss National Science Foundation
Grant: 310030M_182648
Swiss National Science Foundation
Grant: 310030B_176405
NIGMS NIH HHS
Grant: R01 GM123455
NIGMS NIH HHS
Grant: R01 GM123456
Swiss National Science Foundation
Grant: 176405
Directed evolution of enzyme structure and function
Swiss National Science Foundation
Grant: 182648
Exploring structure, function, and mechanism of atypical bacterial chorismate mutases
Swiss National Science Foundation
Swiss National Science Foundation
FWCI
15.58
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
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Additional file 1 of SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering
Additional file 1 of MBE: model-based enrichment estimation and prediction for differential sequencing data
Additional file 1 of MBE: model-based enrichment estimation and prediction for differential sequencing data
Additional file 2 of MBE: model-based enrichment estimation and prediction for differential sequencing data
Additional file 2 of MBE: model-based enrichment estimation and prediction for differential sequencing data
Additional file 2 of SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering
Additional file 3 of SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering
Additional file 2 of SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering
Additional file 3 of SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering