A Jump-Distance-Based Parameter Inference Scheme for Particulate Trajectories.

ABSTRACT: This study presents an improved quantitative tool for the analysis of particulate trajectories. Particulate trajectory data appears in several different biological contexts, from the trajectory of chemotaxing bacteria to the nuclear mobility inferred from the trajectory of MS2 spots. Presently, the majority of analyses performed on particulate trajectory data have been limited to mean-squared displacement (MSD) analysis. Although simple, MSD analysis has several pitfalls, including difficulty in selecting between competing methods of motion, handling systems with multiple distinct subpopulations, and parameter extraction from limited time-series data. Here, we provide an alternative to MSD analysis using the jump distance distribution (JDD), which addresses the aforementioned issues. In pa

SUBMITTER: Menssen R 

PROVIDER: S-EPMC6626843 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature