An introduction to Markov State Models and their application to long timescale molecular simulation
 Responsibility
 Gregory R. Bowman, Vijay S. Pande, Frank Noé, editors.
 Language
 English.
 Publication
 Dordrecht : Springer, 2014.
 Physical description
 1 online resource (xii, 139 pages) : illustrations (some color).
 Series
 Advances in experimental medicine and biology v.797. 00652598
Access
Available online
More options
Creators/Contributors
 Contributor
 Bowman, Gregory R., editor.
 Pande, Vijay S., editor.
 Noé, Frank, editor.
Contents/Summary
 Contents

 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.
 Summary
 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 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 highresolution models capable of quantitative agreement with (or prediction of) experiment to lowresolution 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.
Subjects
Bibliographic information
 Publication date
 2014
 Series
 Advances in Experimental Medicine and Biology, 00652598 ; volume 797
 Available in another form
 Printed edition: ( 9789400776050 )
 ISBN
 9789400776067 (electronic bk.)
 9400776063 (electronic bk.)
 9789400776050
 9400776055 (print)
 9789400776050 (print)