Fall Seminar Series - October 23, 2003
University
of Minnesota
School
of Statistics
College
of Liberal Arts
Statistical Analysis of Single
Molecule Experiments in Chemistry
Samuel Kou
Department of Statistics
Harvard University
Thursday, October 23, 2003
4:00 PM, 115
Ford Hall
Minneapolis, East Bank Campus
Social at 3:30 PM, 300
Ford Hall
Abstract
Recent technological advances allow scientists for the first time
to follow a biochemical process on a single molecule basis, which, unlike
traditional macroscopic experiments, raises many challenging data-analysis
problems and calls for a sophisticated statistical modeling and inference
effort. This paper provides the first likelihood-based analysis of the single-molecule
fluorescence lifetime experiment, in which the conformational dynamics of
a single DNA hairpin molecule is of interest. The conformational change is
modeled as a continuous-time two-state Markov chain, which is not directly
observable and has to be inferred from changes in photon emissions from a
dye attached to the DNA hairpin molecule. In addition to the hidden Markov
structure, the presence of molecular Brownian diffusion further complicates
the matter. We show that closed form likelihood function can be obtained and
a Metropolis-Hastings algorithm can be applied to compute the posterior distribution
of the parameters of interest. The data augmentation technique is utilized
to handle both the Brownian diffusion and the issue of model discrimination.
Our results increase the estimating resolution by several folds. The success
of this analysis indicates there is an urgent need to bring modern statistical
techniques to the analysis of data produced by modern technologies.
This work is joint with Sunney Xie and Jun Liu.