Computational Stability Modeling

Computational Stability Modeling is a computational methodology that predicts and analyzes the structural and functional resilience of biocatalysts under varying environmental conditions by integrating molecular simulations, machine learning, and thermodynamic principles to quantify stability determinants at the atomic or sequence level.

96

Publications

5.1K

Citations

384

Authors

186

Institutions

Publications per year

2017–2026

39

Authors

384

  1. PА
    Pavel А. Akimov

    Moscow State University of Civil Engineering, Russia

    3 publications · 98 citations

    3

    h-index

  2. MH
    Mu He

    Duke University, United States

    2 publications · 93 citations

    2

    h-index

  3. RG
    Robert G. Kelly

    University of Virginia, United States

    2 publications · 111 citations

    2

    h-index

  4. RB
    Richard Bonneau

    New York University, United States

    2 publications · 104 citations

    2

    h-index

  5. KK
    Kent Kirshenbaum

    New York University, United States

    2 publications · 104 citations

    2

    h-index

1–5 of 384

Venues

  1. Journal of the American Chemical Society

    JACS · 3 publications · 217 citations

    3

    h-index

  2. Protein Science

    PS · 2 publications · 43 citations

    2

    h-index

  3. Advanced materials research

    AMR · 2 publications · 48 citations

    2

    h-index

  4. Chemistry - A European Journal

    2 publications · 40 citations

    2

    h-index

  5. Nature Communications

    2 publications · 97 citations

    2

    h-index

1–5