Journal
JOURNAL OF THEORETICAL BIOLOGY
Volume 257, Issue 3, Pages 460-474Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jtbi.2008.12.020
Keywords
Bayesian inference; Markov model
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Funding
- NIDCR NIH HHS [R01DE016999-01, DE14756] Funding Source: Medline
- NIDDK NIH HHS [DK54568] Funding Source: Medline
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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. (C) 2009 Elsevier Ltd. All rights reserved.
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