Titlebook: An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation; Gregory R. Bowman,Vijay S. Pande,Fran

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Uncertainty Estimation,s direct comparison with experiments as well as the elucidation of mechanistic pathways for an inherently stochastic process. A vital part of meaningful comparison with experiment is the characterization of the statistical uncertainty in the predicted experimental measurement, which may take the for

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Analysis of Markov Models,operties of the molecular system studied, approximated on the discrete state space. Thus, many quantities of interest to the molecular scientist can now be calculated from the Markov model transition matrix rather than from a “direct” analysis of the underlying simulation data. The advantage over a

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Textbook 2014tanding. 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 effic

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