Bayesian inference-driven model parameterization and model selection for 2CLJQ fluid models

Owen C Madin, Simon Boothroyd, Richard A Messerly, John D Chodera, Josh Fass, and Michael R Shirts
Preprint ahead of publication: [arXiv]

Here, we show how Bayesian inference can be used to automatically perform model selection and fit parameters for a molecular mechanics force field.

Probability distributions of molecular observables computed from Markov models. II. Uncertainties in observables and their time-evolution

John D. Chodera and Frank Noé.
J. Chem. Phys. 133:105102, 2010. [DOI] [PDF]

A simple Bayesian approach for the modeling of statistical uncertainties in kinetic and equilibrium quantities computed from Markov state models of biomolecular dynamics.

Bayesian comparison of Markov models of molecular dynamics with detailed balance constraint

Sergio Bacallado, John D. Chodera, and Vijay S. Pande.
J. Chem. Phys. 131:045106, 2009. [DOI] [PDF] 

A Bayesian scheme for comparing state space decompositions for Markov state models of biomolecular dynamics that incorporates the fact that physical systems must obey detailed balance.  This paper utilizes recent results from Markov chain theory on edge-reinforced random walks.