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Biophys J, April 2002, p. 1930-1942, Vol. 82, No. 4
*Schlumberger-Doll Research, Ridgefield, Connecticut 06877 USA; and
Department of Cellular and Molecular Physiology, Yale
University, New Haven, Connecticut 06520 USA
Hidden Markov models have recently been used to model
single ion channel currents as recorded with the patch clamp technique from cell membranes. The estimation of hidden Markov models parameters using the forward-backward and Baum-Welch algorithms can be performed at signal to noise ratios that are too low for conventional single channel kinetic analysis; however, the application of these algorithms relies on the assumptions that the background noise be white and that
the underlying state transitions occur at discrete times. To address
these issues, we present an "H-noise" algorithm that accounts for correlated background noise and the randomness of sampling
relative to transitions. We also discuss three issues that arise in the
practical application of the algorithm in analyzing single channel
data. First, we describe a digital inverse filter that removes the
effects of the analog antialiasing filter and yields a sharp frequency
roll-off. This enhances the performance while reducing the
computational intensity of the algorithm. Second, the data may be
contaminated with baseline drifts or deterministic interferences such
as 60-Hz pickup. We propose an extension of previous results to
consider baseline drift. Finally, we describe the extension of the
algorithm to multiple data sets.
Biophys J, April 2002, p. 1930-1942, Vol. 82, No. 4
© 2002 by the Biophysical Society 0006-3495/02/04/1930/13 $2.00
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