Notice bibliographique
- Notice
Type(s) de contenu et mode(s) de consultation : Texte noté : électronique
Titre(s) : An introduction to Markov state models and their application to long timescale molecular simulation [Texte électronique] / Gregory R. Bowman, Vijay S. Pande, Frank Noé, editors
Publication : Dordrecht : Springer, [2014]
Description matérielle : 1 ressource dématérialisée
Collection : Advances in experimental medicine and biology ; volume 797
Note(s) : Includes bibliographical references
"The aim of this book volume is to explain the importance of Markov state models to
molecular simulation, how they work, and how they can be applied to a range of problems.
The Markov state model (MSM) approach aims to address two key challenges of molecular
simulation: 1) How to reach long timescales using short simulations of detailed molecular
models [and] 2) How to systematically gain insight from the resulting sea of data.
MSMs do this by providing a compact representation of the vast conformational space
available to biomolecules by decomposing it into states-sets of rapidly interconverting
conformations-and the rates of transitioning between states. This kinetic definition
allows one to easily vary the temporal and spatial resolution of an MSM from high-resolution
models capable of quantitative agreement with (or prediction of) experiment to low-resolution
models that facilitate understanding. Additionally, MSMs facilitate the calculation
of quantities that are difficult to obtain from more direct MD analyses, such as the
ensemble of transition pathways. This book introduces the mathematical foundations
of Markov models, how they can be used to analyze simulations and drive efficient
simulations, and some of the insights these models have yielded in a variety of applications
of molecular simulation"--Publisher's description
Autre(s) auteur(s) : Bowman, Gregory R.. Fonction indéterminée
Pande, Vijay. Fonction indéterminée
Noé, Frank. Fonction indéterminée
Sujet(s) : Markov, Processus de
Identifiants, prix et caractéristiques : ISBN 9789400776067
Identifiant de la notice : ark:/12148/cb44722575d
Notice n° :
FRBNF44722575
(notice reprise d'un réservoir extérieur)
Table des matières : An overview and practical guide to building Markov state models ; Markov model theory
; Estimation and validation of Markov models ; Uncertainty estimation ; Analysis
of Markov models ; Transition path theory ; Understanding protein folding using
Markov state models ; Understanding molecular recognition by kinetic network models
constructed from molecular dynamics simulations ; Markov state and diffusive stochastic
models in electron spin resonance ; Software for building Markov state models.