Concepedia

Machine Learning-guided Directed Evolution

Machine Learning-Guided Directed Evolution is a computational-experimental framework that integrates machine learning models to predict and optimize enzyme variants in directed evolution campaigns by guiding the exploration of sequence space toward functional phenotypes more efficiently than random or traditional methods.

26

Publications

2.5K

Citations

122

Authors

56

Institutions

Publications per year

2017–2026

24

Parents

Publications

26

Machine learning-assisted directed protein evolution with combinatorial libraries

Zachary Wu, S. B. Jennifer Kan, Russell D. Lewis et al. · Proceedings of the National Academy of Sciences · 2019 · 619 citations · Full text

, , +17

Low-N protein engineering with data-efficient deep learning

Surojit Biswas, Grigory Khimulya, Ethan C. Alley et al. · Nature Methods · 2021 · 417 citations

, , +14

Informed training set design enables efficient machine learning-assisted directed protein evolution

Bruce J. Wittmann, Yisong Yue, Frances H. Arnold · Cell Systems · 2021 · 218 citations · Full text

, , +12

Machine-Learning-Guided Mutagenesis for Directed Evolution of Fluorescent Proteins

Yutaka Saitō, Misaki Oikawa, Hikaru Nakazawa et al. · ACS Synthetic Biology · 2018 · 171 citations

, , +15

Rapid in silico directed evolution by a protein language model with EVOLVEpro

Kaiyi Jiang, Zhaoqing Yan, Matteo Di Bernardo et al. · Science · 2024 · 156 citations

, , +13

1–5 of 26

Authors

122

  1. FH
    Frances H. Arnold

    California Institute of Technology, United States

    6 publications · 981 citations

    6

    h-index

  2. YY
    Yisong Yue

    California Institute of Technology, United States

    4 publications · 323 citations

    4

    h-index

  3. GM
    George M. Church

    Harvard University, United States

    3 publications · 508 citations

    3

    h-index

  4. JY
    Jason Yang

    California Institute of Technology, United States

    3 publications · 130 citations

    3

    h-index

  5. BJ
    Bruce J. Wittmann

    California Institute of Technology, United States

    3 publications · 851 citations

    3

    h-index

1–5 of 122

Institutions

56

  1. California Institute of Technology

    Pasadena, United States

    6 h-index

    32 publications

    4.7K citations

  2. Massachusetts Institute of Technology

    Cambridge, United States

    3 h-index

    6 publications

    1.3K citations

  3. The University of Tokyo

    Tokyo, Japan

    3 h-index

    5 publications

    621 citations

  4. National Institute of Advanced Industrial Science and Technology

    Tsukuba, Japan

    2 h-index

    4 publications

    480 citations

  5. Tohoku University

    Sendai, Japan

    2 h-index

    9 publications

    1K citations

  6. National Institute for Materials Science

    Tsukuba, Japan

    2 h-index

    2 publications

    240 citations

  7. Michigan State University

    East Lansing, United States

    2 h-index

    5 publications

    273 citations

  8. Division of Chemistry

    Arlington, United States

    2 h-index

    4 publications

    44 citations

1–8 of 56

Venues

  1. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 6 publications · 145 citations

    6

    h-index

  2. Proceedings of the National Academy of Sciences

    PNAS · 2 publications · 658 citations

    2

    h-index

  3. Nature Communications

    2 publications · 148 citations

    2

    h-index

  4. Journal of drug targeting

    1 publications · 18 citations

    1

    h-index

  5. ACS Synthetic Biology

    1 publications · 171 citations

    1

    h-index

1–5