Document Detail


Single-channel data and missed events: analysis of a two-state Markov model.
MedLine Citation:
PMID:  1704138     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Patch-clamp recording permits investigation of the gating kinetics of single ion channels. Careful statistical analysis of kinetic data can yield clues as to the molecular events underlying channel gating. However, it is important that such analysis should take full account of the limitations that arise from the finite time resolution of patch-clamp recording techniques. Single-ion-channel data are generally interpreted in terms of Markov process models of channel gating mechanisms. Experimental channel records suffer from time interval omission, i.e. failure to detect brief channel openings and closings. This leads to an identifiability problem when analysing single-channel data, i.e. different gating mechanisms provide equally convincing descriptions of the same experimental data. We consider a two-state Markov model of receptor-channel gating in which the channel opening rate is proportional to the agonist concentration, C in equilibrium with OA. By using computer-simulated data, the approximate likelihood of the data is maximized to yield parameter estimates for the model. At a single agonist concentration there is an identifiability problem in that two pairs of parameter estimates are obtained. The 'true' parameter estimates cannot be distinguished from the 'false' ones. By considering data corresponding to a range of agonist concentrations one may identify the 'true' parameter estimates as those that do not change as the agonist concentration is increased. Alternatively, one may identify the 'true' parameter estimates directly by maximizing a global likelihood, the latter being obtained by simultaneous consideration of data obtained at several different agonist concentrations.(ABSTRACT TRUNCATED AT 250 WORDS)
Authors:
F G Ball; S S Davies; M S Sansom
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Proceedings. Biological sciences / The Royal Society     Volume:  242     ISSN:  0962-8452     ISO Abbreviation:  Proc. Biol. Sci.     Publication Date:  1990 Oct 
Date Detail:
Created Date:  1991-03-08     Completed Date:  1991-03-08     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  101245157     Medline TA:  Proc Biol Sci     Country:  ENGLAND    
Other Details:
Languages:  eng     Pagination:  61-7     Citation Subset:  IM    
Affiliation:
Department of Mathematics, University of Nottingham, University Park, U.K.
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MeSH Terms
Descriptor/Qualifier:
Animals
Computer Simulation
Ion Channels / drug effects,  metabolism*
Kinetics
Likelihood Functions
Markov Chains
Models, Biological*
Chemical
Reg. No./Substance:
0/Ion Channels

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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