Inferring Microscopic Kinetic Rates from Stationary State Distributions.

Purushottam D Dixit, Ken A Dill
Author Information
  1. Purushottam D Dixit: Department of Systems Biology, Columbia University , New York, New York 10032, United States.
  2. Ken A Dill: Department of Systems Biology, Columbia University , New York, New York 10032, United States.

Abstract

We present a principled approach for estimating the matrix of microscopic transition probabilities among states of a Markov process, given only its stationary state population distribution and a single average global kinetic observable. We adapt Maximum Caliber, a variational principle in which the path entropy is maximized over the distribution of all possible trajectories, subject to basic kinetic constraints and some average dynamical observables. We illustrate the method by computing the solvation dynamics of water molecules from molecular dynamics trajectories.

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Grants

  1. R01 GM090205/NIGMS NIH HHS

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