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The Resource An introduction to Markov State Models and their application to long timescale molecular simulation, Gregory R. Bowman, Vijay S. Pande, Frank Noé, editors

An introduction to Markov State Models and their application to long timescale molecular simulation, Gregory R. Bowman, Vijay S. Pande, Frank Noé, editors

Editor
Contributor
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 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
Language
eng
Work
Publication
Extent
1 online resource (xii, 139 pages)
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
Isbn
9789400776067
Instance
Label
An introduction to Markov State Models and their application to long timescale molecular simulation
Title
An introduction to Markov State Models and their application to long timescale molecular simulation
Statement of responsibility
Gregory R. Bowman, Vijay S. Pande, Frank Noé, editors
Contributor
Editor
Subject
Language
eng
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 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
Member of
Cataloging source
GW5XE
Dewey number
519.2/33
Illustrations
illustrations
Index
no index present
LC call number
QA274.7
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
NLM call number
  • W1
  • QA 274.7
NLM item number
AD559 v.797 2014
http://library.link/vocab/relatedWorkOrContributorName
  • Bowman, Gregory R.
  • Pande, Vijay
  • Noé, Frank
Series statement
Advances in Experimental Medicine and Biology,
Series volume
volume 797
http://library.link/vocab/subjectName
  • Markov processes
  • Biology
  • Time Factors
  • Molecular Dynamics Simulation
  • Biology
  • Markov Chains
  • Biology
  • Markov processes
Label
An introduction to Markov State Models and their application to long timescale molecular simulation, Gregory R. Bowman, Vijay S. Pande, Frank Noé, editors
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
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
Control code
870680524
Dimensions
unknown
Extent
1 online resource (xii, 139 pages)
File format
unknown
Form of item
online
Isbn
9789400776067
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
  • 10.1007/978-94-007-7606-7
  • 10.1007/978-94-007-7
Other physical details
illustrations (some color)
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)870680524
Label
An introduction to Markov State Models and their application to long timescale molecular simulation, Gregory R. Bowman, Vijay S. Pande, Frank Noé, editors
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
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
Control code
870680524
Dimensions
unknown
Extent
1 online resource (xii, 139 pages)
File format
unknown
Form of item
online
Isbn
9789400776067
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
  • 10.1007/978-94-007-7606-7
  • 10.1007/978-94-007-7
Other physical details
illustrations (some color)
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)870680524

Subject

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