Kinetic Network Models

Kinetic Network Model is a computational framework that represents protein conformational dynamics as a graph-based Markov process, where nodes correspond to metastable conformational states and edges encode transition probabilities derived from kinetic data, enabling the quantitative modeling of time-dependent structural transitions in biomolecules.

184

Publications

9.7K

Citations

523

Authors

288

Institutions

Publications per year

2017–2026

44

Variants

Kinetic Network Model

Authors

523

  1. XH
    Xuhui Huang

    Hong Kong University of Science and Technology, Hong Kong SAR China

    7 publications · 238 citations

    7

    h-index

  2. DJ
    David J. Wales

    University of Cambridge, United Kingdom

    6 publications · 169 citations

    6

    h-index

  3. RM
    Ronald M. Levy

    Rutgers, The State University of New Jersey, United States

    5 publications · 383 citations

    5

    h-index

  4. MA
    Michael Andrec

    Rutgers, The State University of New Jersey, United States

    4 publications · 326 citations

    4

    h-index

  5. DS
    David S. Soong

    University of California, Berkeley, United States

    4 publications · 88 citations

    4

    h-index

1–5 of 523

Venues

  1. The Journal of Physical Chemistry B

    11 publications · 293 citations

    11

    h-index

  2. The Journal of Chemical Physics

    9 publications · 1.3K citations

    9

    h-index

  3. Proceedings of the National Academy of Sciences

    PNAS · 8 publications · 1.2K citations

    8

    h-index

  4. PLoS Computational Biology

    7 publications · 249 citations

    7

    h-index

  5. Bioinformatics

    7 publications · 282 citations

    7

    h-index

1–5