Markov State Models: From an Art to a Science.

By Brooke E. Husic, Vijay S. Pande. Journal of the American Chemical Society, 2018

800 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/260f212da0cf8b3309f0ab3a130a0ad22993892e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. G. de Fabritiis
2. Tony Lelièvre
3. Frank No'e
4. Jiang Wang
5. Cecilia Clementi
6. Brooke E. Husic

In Molecular Biology

1. Frank No'e
2. Cecilia Clementi
3. Brooke E. Husic
4. Jiang Wang
5. G. de Fabritiis
6. J'erome H'enin
7. Tony Lelièvre
8. Lucie Delemotte

In Spectroscopy

1. Cecilia Clementi
2. Frank No'e
3. G. de Fabritiis
4. Tony Lelièvre
5. Michael R. Shirts
6. J'erome H'enin
7. Lucie Delemotte
8. Brooke E. Husic

Citations in the corpus

• Coarse graining molecular dynamics with graph neural networks. (2020, methodology): “A great deal of research has gone into MSM theory and practice which is summarized in books 81,82 and recent reviews 56,83 .”
• Enhanced Sampling Methods for Molecular Dynamics Simulations [Article v1.0] (2022, methodology): “It generally takes advantage of analysis methods such as Markov State Modeling (MSM) to then stitch together trajectories and build a coherent model of, not only the equilibrium population of metastable states, but also the rates of conversion between these states [306, 307].”