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Efficient Computation, Sensitivity and Error Analysis of Committor Probabilities for Complex Dynamical Processes

Please always quote using this URN:urn:nbn:de:0296-matheon-11034
  • In many fields of physics, chemistry and biology the characterization of dynamical processes between states or species is of fundamental interest. The central mathematical function in such sit- uations is the committor probability - a generalized reaction coordinate that measures the progress of the process of interest as the probability of proceeding towards the target state rather than re- lapsing to the source state. Here, we present methodology for the efficient computation of com- mittor probabilities for large-scale systems, such as, for example simuations of biomolecular fold- ing. A method is derived for computing the committor for discrete state spaces using eigenvectors with expressions for the sensitivity and a Bayesian error model for the committor. The concepts are illustrated on two examples of diffusive dynamics with a very large number of states: a two- dimensional model potential with three minima, and a three-dimensional model representing protein-ligand binding. The method can finally be used to compute committor probabilities in- cluding error estimations for medium and large system sizes allowing access to the apparatus of transition path theory and its applications.

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Metadaten
Author:Jan-Hendrik Prinz, Martin Held, Jeremy C. Smith, Frank Noe
URN:urn:nbn:de:0296-matheon-11034
Referee:Christof Schütte
Document Type:Preprint, Research Center Matheon
Language:English
Date of first Publication:2012/05/18
Release Date:2012/05/18
Institute:Research Center Matheon
Freie Universität Berlin
MSC-Classification:62-XX STATISTICS / 62Mxx Inference from stochastic processes / 62M05 Markov processes: estimation
Preprint Number:959
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