Inferring the parameters of random walks without tracking

EVENT : C3BI Seminars


Main speaker : Till Kletti, from Former member of the Decision and Bayesian Computation Group at the DBC Date : 30-01-2020 at 02:00 pm Location : Auditorium Francois Jacob – BIME (26), Institut Pasteur, Paris


We consider the problem of inferring random walk models (e.g. spatial maps of diffusivity, drift) of a set of moving particles (e.g. biomolecules) using discrete-time snapshots of their positions (a movie). A main difficulty stems from the fact that the particles are not labelled, which makes the particle matching between two consecutive snapshots uncertain. We describe how to account for this uncertainty using the belief propagation (BP) algorithm, which outperforms explicit tracking methods when the particle density is high. Furthermore, we describe procedures allowing us to account for blinking of the particles. Finally, we show applications of the method to mapping heterogeneous diffusivity fields experienced by biomolecules in the plasma membrane of living cells.


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