Dense mapping of intracellular diffusion and drift from single-particle tracking data analysis

Antoine Salomon (1) , Cesar Augusto Valades Cruz (1, 2) , Ludovic Leconte (2) , Charles Kervrann (1)

1 SERPICO - Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes
2 Biologie Cellulaire et Cancer

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.

Domaines: Traitement des images [eess.IV]; Physique mathématique [math-ph]; Optique / photonique

Antoine Salomon, Cesar Augusto Valades Cruz, Ludovic Leconte, Charles Kervrann. Dense mapping of intracellular diffusion and drift from single-particle tracking data analysis. ICASSP 2020 - IEEE International Conference on Acoustics, Speech and Signal Processing, May 2020, Barcelona, Spain. pp.1-5. ⟨hal-03087048⟩