title: Communication: A multiscale Bayesian inference approach to analyzing subdiffusion in particle trajectories.
abstract: Anomalous diffusion is characterized by its asymptotic behavior for t → ∞. This makes it difficult to detect and describe in particle trajectories from experiments or computer simulations, which are necessarily of finite length. We propose a new approach using Bayesian inference applied directly to the observed trajectories sampled at different time scales. We illustrate the performance of this approach using random trajectories with known statistical properties and then use it for analyzing the motion of lipid molecules in the plane of a lipid bilayer.
authors: Centre de Biophysics. Moléculaire, CNRS, Rue Charles Sadron, 45071 Orléans, France.
authors: Konrad
authors: K
authors: Hinsen
authors: Centre de Biophysics. Moléculaire, CNRS, Rue Charles Sadron, 45071 Orléans, France.
authors: Gerald R
authors: GR
authors: Kneller
mesh_terms: D001499:Bayes Theorem; D003198:Computer Simulation; D004058:Diffusion; D008051:Lipid Bilayers / Q000737:chemistry; D008055:Lipids / Q000737:chemistry; D008954:Models, Biological
chemical_list: D008051:Lipid Bilayers; D008055:Lipids