Predicting mutant outcome by combining deep mutational scanning and machine learning-Reference-Cited by-同舟云学术

Predicting mutant outcome by combining deep mutational scanning and machine learning

Published:2021-07-31 Issue:1 Volume:90 Page:45-57
ISSN:0887-3585
Container-title:Proteins: Structure, Function, and Bioinformatics
language:en
Short-container-title:Proteins

Author:

Sarfati Hagit¹,Naftaly Si²,Papo Niv²^ORCID,Keasar Chen¹^ORCID

Affiliation:

1. Department of Computer Science Ben‐Gurion University of the Negev Be'er Sheva Israel

2. Avram and Stella Goldstein‐Goren Department of Biotechnology Engineering and the National Institute of Biotechnology in the Negev Ben‐Gurion University of the Negev Be'er Sheva Israel

Funder

H2020 European Research Council

Israel Science Foundation

Publisher

Wiley

Subject

Molecular Biology,Biochemistry,Structural Biology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/prot.26184

Reference44 articles.

1. Stability engineering of the human antibody repertoire

2. Protein stability engineering insights revealed by domain-wide comprehensive mutagenesis

3. Machine-learning-guided directed evolution for protein engineering

4. Insulin and its analogs: actions via insulin and IGF receptors

5. Protein Thermostability Calculations Using Alchemical Free Energy Simulations

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