Model comparison for single particle tracking in biological fluids
Year: 2014
Type: preprint
Abstract: State-of-the-art techniques in particle tracking microscopy provide high-resolution path trajectories for the dynamical analysis of diverse foreign particles in biological fluids. For particles on the order of one micron in diameter, these paths are not generally consistent with simple Brownian motion. Despite an abundance of data confirming these findings, stochastic modeling of the complex particle motion has received comparatively little attention. Yet, prediction beyond experimental time scales -- such as first-passage times through biological barriers -- is a fundamental scientific objective that requires a careful statistical approach. Even among existing candidate models, few attempts have been made at likelihood-based model comparisons and other quantitative evaluations. In this article, we employ a robust Bayesian methodology to address this gap. We analyze two competing models -- fractional Brownian motion (fBM) and a generalized Langevin equation (GLE) consistent with viscoelastic theory -- applied to an ensemble of 30 second paths of 1 micron diameter tracer particles in human lung mucus. We conclude that either fBM or a GLE with a long memory spectrum are favored by the data, whereas GLEs with small to moderate memory spectra are insufficient.
Source: arXiv (Cornell University)
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W121453640