ScienceOpen:
research and publishing network
For Publishers
Discovery
Metadata
Peer review
Hosting
Publishing
For Researchers
Join
Publish
Review
Collect
My ScienceOpen
Sign in
Register
Dashboard
Blog
About
Search
Advanced search
My ScienceOpen
Sign in
Register
Dashboard
Search
Search
Advanced search
For Publishers
Discovery
Metadata
Peer review
Hosting
Publishing
For Researchers
Join
Publish
Review
Collect
Blog
About
13
views
0
references
Top references
cited by
74
Cite as...
0 reviews
Review
0
comments
Comment
0
recommends
+1
Recommend
0
collections
Add to
0
shares
Share
Twitter
Sina Weibo
Facebook
Email
3,356
similar
All similar
Record
: found
Abstract
: not found
Book
: not found
An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation
other
Editor(s):
Gregory R. Bowman
,
Vijay S. Pande
,
Frank Noé
Publication date
(Print):
2014
Publisher:
Springer Netherlands
Read this book at
Publisher
Buy book
Review
Review book
Invite someone to review
Bookmark
Cite as...
There is no author summary for this book yet. Authors can add summaries to their books on ScienceOpen to make them more accessible to a non-specialist audience.
Related collections
An Introduction to SAXS
Author and book information
Book
ISBN (Print):
978-94-007-7605-0
ISBN (Electronic):
978-94-007-7606-7
Publication date (Print):
2014
DOI:
10.1007/978-94-007-7606-7
SO-VID:
8d23f98b-511c-4e10-b634-50b6ecda11bd
License:
http://www.springer.com/tdm
History
Data availability:
Comments
Comment on this book
Sign in to comment
Book chapters
pp. 1
Introduction and Overview of This Book
pp. 7
An Overview and Practical Guide to Building Markov State Models
pp. 23
Markov Model Theory
pp. 45
Estimation and Validation of Markov Models
pp. 61
Uncertainty Estimation
pp. 75
Analysis of Markov Models
pp. 91
Transition Path Theory
pp. 101
Understanding Protein Folding Using Markov State Models
pp. 107
Understanding Molecular Recognition by Kinetic Network Models Constructed from Molecular Dynamics Simulations
pp. 115
Markov State and Diffusive Stochastic Models in Electron Spin Resonance
pp. 139
Software for Building Markov State Models
Similar content
3,356
The structure and timescales of heat perception in larval zebrafish.
Authors:
Martin Haesemeyer
,
Drew N Robson
,
Jennifer M Li
…
Detection of timescales in evolving complex systems
Authors:
Richard K. Darst
,
Clara Granell
,
Alex Arenas
…
Emergent timescales in entangled quantum dynamics of ultracold molecules in optical lattices
Authors:
M. Wall
,
L. Carr
See all similar
Cited by
70
Major Histocompatibility Complex (MHC) Class I and MHC Class II Proteins: Conformational Plasticity in Antigen Presentation
Authors:
Marek Wieczorek
,
Esam T. Abualrous
,
Jana Sticht
…
Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics
Authors:
Frank Noé
,
Christoph Wehmeyer
Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations.
Authors:
Stefan Klus
,
Peter J. Koltai
,
Frank Noé
…
See all cited by