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) |
|---|---|
| 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 |
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ASJC Scopus subject areas
- Biophysics
Cite this
Improved hidden Markov models for molecular motors, part 1 : Basic theory. / Müllner, Fiona E.; Syed, Sheyum; Selvin, Paul R.; Sigworth, Fred J.
In: Biophysical Journal, Vol. 99, No. 11, 01.12.2010, p. 3684-3695.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Improved hidden Markov models for molecular motors, part 1
T2 - Basic theory
AU - Müllner, Fiona E.
AU - Syed, Sheyum
AU - Selvin, Paul R.
AU - Sigworth, Fred J.
PY - 2010/12/1
Y1 - 2010/12/1
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=78649813624&partnerID=8YFLogxK
U2 - 10.1016/j.bpj.2010.09.067
DO - 10.1016/j.bpj.2010.09.067
M3 - Article
C2 - 21112293
AN - SCOPUS:78649813624
VL - 99
SP - 3684
EP - 3695
JO - Biophysical Journal
JF - Biophysical Journal
SN - 0006-3495
IS - 11
ER -