Recombination-based Shuffling

Recombination-Based Shuffling is a computational method within iterative selection cycles that integrates genetic recombination principles to systematically rearrange and recombine constituent elements of candidate solutions, thereby generating novel variants while preserving structural coherence and enhancing search efficiency in solution space exploration.

8

Publications

484

Citations

24

Authors

13

Institutions

Publications per year

2017–2026

1

Authors

24

  1. AM
    Anna Marie Aguinaldo

    California Institute of Technology, United States

    2 publications · 48 citations

    2

    h-index

  2. FH
    Frances H. Arnold

    California Institute of Technology, United States

    2 publications · 48 citations

    2

    h-index

  3. DK
    Dingyue Khor

    University of British Columbia, Canada

    1 publications · 20 citations

    1

    h-index

  4. GR
    Gilles Ravot

    Sanofi (France), France

    1 publications · 29 citations

    1

    h-index

  5. DS
    Deepak Sharma

    Institute of Microbial Technology, India

    1 publications · 20 citations

    1

    h-index

1–5 of 24

Venues

  1. Humana Press eBooks

    Ebook platform · 2 publications · 48 citations

    2

    h-index

  2. RNA

    1 publications · 34 citations

    1

    h-index

  3. Protein Science

    PS · 1 publications · 20 citations

    1

    h-index

  4. Nature Communications

    1 publications · 113 citations

    1

    h-index

  5. Protein Engineering Design and Selection

    PEDS · 1 publications · 29 citations

    1

    h-index

1–5