NOBIAS: Analyzing anomalous diffusion in single-molecule tracks with nonparametric Bayesian inference.

ABSTRACT: Single particle tracking (SPT) enables the investigation of biomolecular dynamics at a high temporal and spatial resolution in living cells, and the analysis of these SPT datasets can reveal biochemical interactions and mechanisms. Still, how to make the best use of these tracking data for a broad set of experimental conditions remains an analysis challenge in the field. Here, we develop a new SPT analysis framework: NOBIAS (NOnparametric Bayesian Inference for Anomalous Diffusion in Single-Molecule Tracking), which applies nonparametric Bayesian statistics and deep learning approaches to thoroughly analyze SPT datasets. In particular, NOBIAS handles complicated live-cell SPT data for which: the number of diffusive states is unknown, mixtures of different diffusive populations may exist wi

SUBMITTER: Chen Z 

PROVIDER: S-EPMC9053523 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature