help button home button Biophys. J.
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Qin, F.
Right arrow Articles by Sachs, F.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Qin, F.
Right arrow Articles by Sachs, F.

Biophys J, October 2000, p. 1928-1944, Vol. 79, No. 4

Hidden Markov Modeling for Single Channel Kinetics with Filtering and Correlated Noise

Feng Qin, Anthony Auerbach, and Frederick Sachs

Department of Physiology and Biophysical Sciences, State University of New York at Buffalo, Buffalo, New York 14214 USA

Hidden Markov modeling (HMM) can be applied to extract single channel kinetics at signal-to-noise ratios that are too low for conventional analysis. There are two general HMM approaches: traditional Baum's reestimation and direct optimization. The optimization approach has the advantage that it optimizes the rate constants directly. This allows setting constraints on the rate constants, fitting multiple data sets across different experimental conditions, and handling nonstationary channels where the starting probability of the channel depends on the unknown kinetics. We present here an extension of this approach that addresses the additional issues of low-pass filtering and correlated noise. The filtering is modeled using a finite impulse response (FIR) filter applied to the underlying signal, and the noise correlation is accounted for using an autoregressive (AR) process. In addition to correlated background noise, the algorithm allows for excess open channel noise that can be white or correlated. To maximize the efficiency of the algorithm, we derive the analytical derivatives of the likelihood function with respect to all unknown model parameters. The search of the likelihood space is performed using a variable metric method. Extension of the algorithm to data containing multiple channels is described. Examples are presented that demonstrate the applicability and effectiveness of the algorithm. Practical issues such as the selection of appropriate noise AR orders are also discussed through examples.

Biophys J, October 2000, p. 1928-1944, Vol. 79, No. 4
© 2000 by the Biophysical Society   0006-3495/00/10/1928/17  $2.00


This article has been cited by other articles:


Home page
 J. Gen. Physiol.Home page
L. Ionescu, C. White, K.-H. Cheung, J. Shuai, I. Parker, J. E. Pearson, J. K. Foskett, and D.-O. D. Mak
Mode Switching Is the Major Mechanism of Ligand Regulation of InsP3 Receptor Calcium Release Channels
J. Gen. Physiol., November 26, 2007; 130(6): 631 - 645.
[Abstract] [Full Text] [PDF]

Home page
 Biophys. JHome page
L. Moffatt
Estimation of Ion Channel Kinetics from Fluctuations of Macroscopic Currents
Biophys. J., July 1, 2007; 93(1): 74 - 91.
[Abstract] [Full Text] [PDF]

Home page
 Biophys. JHome page
F. Vanzi, L. Sacconi, and F. S. Pavone
Analysis of Kinetics in Noisy Systems: Application to Single Molecule Tethered Particle Motion
Biophys. J., July 1, 2007; 93(1): 21 - 36.
[Abstract] [Full Text] [PDF]

Home page
 J. Gen. Physiol.Home page
W. Cheng, F. Yang, C. L. Takanishi, and J. Zheng
Thermosensitive TRPV Channel Subunits Coassemble into Heteromeric Channels with Intermediate Conductance and Gating Properties
J. Gen. Physiol., March 26, 2007; 129(3): 191 - 207.
[Abstract] [Full Text] [PDF]

Home page
 Biophys. JHome page
L. S. Milescu, A. Yildiz, P. R. Selvin, and F. Sachs
Extracting Dwell Time Sequences from Processive Molecular Motor Data
Biophys. J., November 1, 2006; 91(9): 3135 - 3150.
[Abstract] [Full Text] [PDF]

Home page
 Biophys. JHome page
S. A. McKinney, C. Joo, and T. Ha
Analysis of Single-Molecule FRET Trajectories Using Hidden Markov Modeling
Biophys. J., September 1, 2006; 91(5): 1941 - 1951.
[Abstract] [Full Text] [PDF]

Home page
 Biophys. JHome page
Y.-K. The, J. Fernandes, M. O. Popa, A. K. Alekov, J. Timmer, and H. Lerche
Modeling of Single Noninactivating Na+ Channels: Evidence for Two Open and Several Fast Inactivated States
Biophys. J., May 15, 2006; 90(10): 3511 - 3522.
[Abstract] [Full Text] [PDF]

Home page
 Physiol. GenomicsHome page
M. J. Correia, T. G. Wood, D. Prusak, T. Weng, K. J. Rennie, and H.-Q. Wang
Molecular characterization of an inward rectifier channel (IKir) found in avian vestibular hair cells: cloning and expression of pKir2.1
Physiol Genomics, October 4, 2004; 19(2): 155 - 169.
[Abstract] [Full Text] [PDF]

Home page
 Biophys. JHome page
F. Qin and L. Li
Model-Based Fitting of Single-Channel Dwell-Time Distributions
Biophys. J., September 1, 2004; 87(3): 1657 - 1671.
[Abstract] [Full Text] [PDF]

Home page
 Biophys. JHome page
J. J. Celentano and A. G. Hawkes
Use of the Covariance Matrix in Directly Fitting Kinetic Parameters: Application to GABAA Receptors
Biophys. J., July 1, 2004; 87(1): 276 - 294.
[Abstract] [Full Text] [PDF]

Home page
 Biophys. JHome page
F. Qin
Restoration of Single-Channel Currents Using the Segmental k-Means Method Based on Hidden Markov Modeling
Biophys. J., March 1, 2004; 86(3): 1488 - 1501.
[Abstract] [Full Text] [PDF]


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2000 by the Biophysical Society.