ICASSP 2020accepted0 citations
Dense Mapping of Intracellular Diffusion and Drift from Single-Particle Tracking Data Analysis
Antoine Salomon, Cesar Augusto Valades-Cruz, Ludovic Leconte, Charles Kervrann
Abstract
It is of primary interest for biologists to be able to visualize the dynamics of proteins within the cell. In this paper, we propose a new mapping method to robustly estimate dynamics in the entire cell from particle tracks. To obtain satisfying diffusion and drift maps, we use a spatiotemporal kernel estimator. Trajectory classification data is used as input and allows to automatically label particle movements into three classes: confined motion (or subdiffusion), Brownian motion, and directed motion (or superdiffusion). We then use this information to calculate diffusion coefficient and drift maps separately on each class of motion.
BibTeX
@inproceedings{icassp2020_densemappingofin,
title = {Dense Mapping of Intracellular Diffusion and Drift from Single-Particle Tracking Data Analysis},
author = {Antoine Salomon and Cesar Augusto Valades-Cruz and Ludovic Leconte and Charles Kervrann},
booktitle = {ICASSP 2020},
year = {2020}
}