Wu, H. and Mey, A.S.J.S. and Rosta, E. and Noé, F. (2014) Statistically optimal analysis of statediscretized trajectory data from multiple thermodynamic states. J. Chem. Phys., 141 (21). p. 214106.

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Official URL: http://dx.doi.org/10.1063/1.4902240
Abstract
We propose a discrete transitionbased reweighting analysis method (dTRAM) for analyzing configurationspacediscretized simulation trajectories produced at different thermodynamic states (temperatures, Hamiltonians, etc.) dTRAM provides maximumlikelihood estimates of stationary quantities (probabilities, free energies, expectation values) at any thermodynamic state. In contrast to the weighted histogram analysis method (WHAM), dTRAM does not require data to be sampled from global equilibrium, and can thus produce superior estimates for enhanced sampling data such as parallel/simulated tempering, replica exchange, umbrella sampling, or metadynamics. In addition, dTRAM provides optimal estimates of Markov state models (MSMs) from the discretized statespace trajectories at all thermodynamic states. Under suitable conditions, these MSMs can be used to calculate kinetic quantities (e.g. rates, timescales). In the limit of a single thermodynamic state, dTRAM estimates a maximum likelihood reversible MSM, while in the limit of uncorrelated sampling data, dTRAM is identical to WHAM. dTRAM is thus a generalization to both estimators.
Item Type:  Article 

Subjects:  Physical Sciences 
Divisions:  Department of Mathematics and Computer Science > Institute of Mathematics > Comp. Molecular Biology 
ID Code:  1460 
Deposited By:  BioComp Admin 
Deposited On:  11 Nov 2014 18:11 
Last Modified:  30 Nov 2017 15:13 
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