PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Bayesian method for single molecule, fluorescence burst analysis
Paul Barber, Simon Ameer-Beg, Senthi Pathmananthanan, Mark Rowley and Anthony (Ton) C C Coolen
Biomedical Optics Express Volume 1, pp. 1148-1155, 2010.

Abstract

There is currently great interest in determining physical parameters, e.g. fluorescence lifetime, of individual molecules that inform on environmental conditions, whilst avoiding the artefacts of ensemble averaging. Protein interactions, molecular dynamics and sub-species can all be studied. In a burst integrated fluorescence lifetime (BIFL) experiment, identification of fluorescent bursts from single molecules above background detection is a problem. This paper presents a Bayesian method for burst identification based on model selection and demonstrates the detection of bursts consisting of 10% signal amplitude. The method also estimates the fluorescence lifetime (and its error) from the burst data.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:7660
Deposited By:Anthony (Ton) C C Coolen
Deposited On:17 March 2011