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.
Original language | English (US) |
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Pages (from-to) | 3684-3695 |
Number of pages | 12 |
Journal | Biophysical journal |
Volume | 99 |
Issue number | 11 |
DOIs | |
State | Published - Dec 1 2010 |
Externally published | Yes |
ASJC Scopus subject areas
- Biophysics