Details of Grant 

EPSRC Reference:	GR/J99780/01
Title:	BAYESIAN INFERENCE FOR ION CHANNEL GATING MECHANISMS VIA THE GIBBS SAMPLER
Principal Investigator:	Ball, Professor FG
Other Investigators:	O'hagan, Professor A
Researcher Co-Investigators:
Project Partners:
Department:	Sch of Mathematical Sciences
Organisation:	University of Nottingham
Scheme:	Standard Research (Pre-FEC)
Starts:	01 October 1994	Ends:	31 March 1997	Value (£):	75,086
EPSRC Research Topic Classifications:	Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
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Summary on Grant Application Form
The aim of the proposed research is to develop and implement a Gibbs sampling framework for Bayesian ion channel inference, both a) from reconstructed sojourn time data and b) directly from single channel current records. The principal difficulty with (a) is that the underlying channel process is only partially observed, in that there is both aggregation of states and time interval omission. This can be overcome in a Gibbs sampling framework by including the unobserved information as extra parameters. We will consider a discretised version of (a), in which the underlying continuous time Markov chain, used to model the single channel gating mechanism, is sampled at intervals of length h. A Gibbs sampler algorithm will be developed for simulating from the posterior distribution of , the parameters governing the underlying gating mechanism. The choice of the sampling interval h will be investigated theoretically, using the theory of aggregated semi-Markov processes. The problem of basing inference directly on the single channel current record involves a hierarchical structure and thus clearly lies in the 'domain of attraction' of the Gibbs sampler. The Gibbs sampling framework extends naturally to the situation when the prior specification incorporates a mixture of channel models, thus enabling methods of choosing between several competing models to be explored.
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Organisation Website:	http://www.nottingham.ac.uk