@article{57ef90637c7449c1a1ecf2e2bc476758,
title = "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.",
author = "M{\"u}llner, {Fiona E.} and Sheyum Syed and Selvin, {Paul R.} and Sigworth, {Fred J.}",
year = "2010",
month = dec
day = "1",
doi = "10.1016/j.bpj.2010.09.067",
language = "English (US)",
volume = "99",
pages = "3684--3695",
journal = "Biophysical Journal",
issn = "0006-3495",
publisher = "Biophysical Society",
number = "11",
}