title: Quantitative characterization of changes in dynamical behavior for single-particle tracking studies.
abstract: Single-particle tracking experiments have been used widely to study the heterogeneity of a sample. Segments with dissimilar diffusive behaviors are associated with different intermediate states, usually by visual inspection of the tracking trace. A likelihood-based, systematic approach is presented to remove this incertitude. Maximum likelihood estimators are derived for the determination of diffusion coefficients. A likelihood ratio test is applied to the localization of the changes in them. Simulations suggest that the proposed procedure is statistically robust and is able to quantitatively recover time-dependent changes in diffusion coefficients even in the presence of large measurement noise.
authors.affiliation: Department of Chemistry, University of California at Berkeley, Physical Biosciences Division, Lawrence Berkeley National Laboratories, Berkeley, California 94720, USA.
authors.forename: D
authors.initials: D
authors.lastname: Montiel
authors.forename: H
authors.initials: H
authors.lastname: Cang
authors.forename: H
authors.initials: H
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D016001:Confidence Intervals; D004058:Diffusion; D016013:Likelihood Functions; D018715:Microscopy, Video; D015233:Models, Statistical; D009038:Motion; D053758:Nanoparticles; D013269:Stochastic Processes