title: Bayesian estimation for species identification in single-molecule fluorescence microscopy.
abstract: In this article we describe a recursive Bayesian estimator for the identification of diffusing fluorophores using photon arrival-time data from a single spectral channel. We present derivations for all relevant diffusion and fluorescence models, and we use simulated diffusion trajectories and photon streams to evaluate the estimator's performance. We consider simplified estimation schemes that bin the photon counts within time intervals of fixed duration, and show that they can perform well in realistic parameter regimes. The latter results indicate the feasibility of performing identification experiments in real time. It will be straightforward to generalize our approach for use in more complicated scenarios, e.g., with multiple spectral channels or fast photophysical dynamics.
authors.affiliation: Option of Bioengineering, and Norman Bridge Laboratory of Physics, California Institute of Technology, Pasadena, California 91125, USA. mchale@caltech.edu
authors.forename: Kevin
authors.initials: K
authors.lastname: McHale
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Berglund
authors.forename: Hideo
authors.initials: H
authors.lastname: Mabuchi
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D004058:Diffusion; D008856:Microscopy, Fluorescence; D008962:Models, Theoretical; D017785:Photons; D013223:Statistics as Topic