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Improved hidden Markov models for molecular motors, part 1: basic theory.


ABSTRACT: Hidden Markov models (HMMs) provide an excellent analysis of recordings with very poor signal/noise ratio made from systems such as ion channels which switch among a few states. This method has also recently been used for modeling the kinetic rate constants of molecular motors, where the observable variable-the position-steadily accumulates as a result of the motor's reaction cycle. We present a new HMM implementation for obtaining the chemical-kinetic model of a molecular motor's reaction cycle called the variable-stepsize HMM in which the quantized position variable is represented by a large number of states of the Markov model. Unlike previous methods, the model allows for arbitrary distributions of step sizes, and allows these distributions to be estimated. The result is a robust algorithm that requires little or no user input for characterizing the stepping kinetics of molecular motors as recorded by optical techniques.

SUBMITTER: Mullner FE 

PROVIDER: S-EPMC2998602 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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Improved hidden Markov models for molecular motors, part 1: basic theory.

Müllner Fiona E FE   Syed Sheyum S   Selvin Paul R PR   Sigworth Fred J FJ  

Biophysical journal 20101201 11


Hidden Markov models (HMMs) provide an excellent analysis of recordings with very poor signal/noise ratio made from systems such as ion channels which switch among a few states. This method has also recently been used for modeling the kinetic rate constants of molecular motors, where the observable variable-the position-steadily accumulates as a result of the motor's reaction cycle. We present a new HMM implementation for obtaining the chemical-kinetic model of a molecular motor's reaction cycle  ...[more]

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