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A Python implementation of the multistate Bennett acceptance ratio (MBAR)
Publication Overview
Shirts MR and Chodera JD. Statistically optimal analysis of samples from multiple equilibrium states. J. Chem. Phys. 129:124105 (2008) Publication

Description: A Python implementation of the multistate Bennett acceptance ratio (MBAR) method for estimation of expectations and free energy differences (and their statistical uncertainties) from multiple equilibrium simulations at different thermodynamic states.

Note that pymbar is been migrated to GitHub:
http://github.com/choderalab/pymbar

Available Downloads and Their Potential Uses: A Python implementation of the MBAR estimator is available for download, as well as a number of examples applying MBAR to common applications in computational chemistry.

Purpose/Synopsis: Analyze data from multiple equilibrium simulations at different thermodynamic states

Audience: Computational chemists and statistical physicists

Long Term Goals and Related Uses: This project provides a Python reference implementation of the multistate Bennett acceptance ratio (MBAR) method for the analysis of multiple equilibrium simulations at different thermodynamic states

Ontology Classification: Data_Analysis_Software, Statistical_Analysis
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Keywords: analysis, MBAR, multistate Bennett acceptance ratio, WHAM
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