Markov chain Monte Carlo fitting of single-channel data from inositol trisphosphate receptors

Item Type:	Article
Title:	Markov chain Monte Carlo fitting of single-channel data from inositol trisphosphate receptors
Creators Name:	Gin, E. and Falcke, M. and Wagner, L.E. and Yule, D.I. and Sneyd, J.
Abstract:	In many cell types, the inositol trisphosphate receptor (IPR) is one of the important components that control intracellular calcium dynamics, and an understanding of this receptor (which is also a calcium channel) is necessary for an understanding of calcium oscillations and waves. Recent advances in experimental techniques now allow for the measurement of single-channel activity of the IPR in conditions similar to its native environment, and these data can be used to determine the rate constants in Markov models of the IPR. We illustrate a parameter estimation method based on Markov chain Monte Carlo, which can be used to fit directly to single-channel data, and determining, as an intrinsic part of the fit, the times at which the IPR is opening and closing. We show, using simulated data, the most complex Markov model that can be unambiguously determined from steady-state data and show that non-steady-state data is required to determine more complex models.
Keywords:	Bayesian inference, Markov Model
Source:	Journal of Theoretical Biology
ISSN:	0022-5193
Publisher:	Academic Press
Volume:	257
Number:	3
Page Range:	460-474
Date:	7 April 2009
Official Publication:	https://doi.org/10.1016/j.jtbi.2008.12.020
PubMed:	View item in PubMed

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