Repository: Freie Universität Berlin, Math Department

Gaussian Markov transition models of molecular kinetics

Wu, H. and Noé, F. (2015) Gaussian Markov transition models of molecular kinetics. J. Chem. Phys., 142 (8). 084104.

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The slow processes of molecular dynamics (MD) simulations—governed by dominant eigenvalues and eigenfunctions of MD propagators—contain essential information on structures of and transition rates between long-lived conformations. Existing approaches to this problem, including Markov state models and the variational approach, represent the dominant eigenfunctions as linear combinations of a set of basis functions. However the choice of the basis functions and their systematic statistical estimation are unsolved problems. Here, we propose a new class of kinetic models called Markov transition models (MTMs) that approximate the transition density of the MD propagator by a mixture of probability densities. Specifically, we use Gaussian MTMs where a Gaussian mixture model is used to approximate the symmetrized transition density. This approach allows for a direct computation of spectral components. In contrast with the other Galerkin-type approximations, our approach can automatically adjust the involved Gaussian basis functions and handle the statistical uncertainties in a Bayesian framework. We demonstrate by some simulation examples the effectiveness and accuracy of the proposed approach.

Item Type:Article
Subjects:Physical Sciences
Mathematical and Computer Sciences
Divisions:Department of Mathematics and Computer Science > Institute of Mathematics > Comp. Molecular Biology
ID Code:1503
Deposited By: BioComp Admin
Deposited On:29 Jan 2015 22:13
Last Modified:19 Jun 2017 13:23

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