Talk by Dr. Samuel WK Wong (DSAS colloquium)

Title: Bayesian analysis of coupled cellular and nuclear trajectories for cell migration

Abstract: Cell migration, the process by which cells move from one location to another, plays crucial roles in many biological events.  Most statistical cell migration models are fitted using time-lapse microscopy data from cell trajectories.  Improved imaging techniques have allowed detailed trajectory data for both the cell and its associated nucleus to be recorded.  These data can be used to further our understanding of cell migration, since it is known that the cell and nucleus work together to orchestrate movement.  In this talk, I will present a Bayesian hierarchical model that we developed for a joint analysis of coupled cell-nucleus trajectories.  We use a bivariate angular distribution to handle the cell-nucleus coupling, and introduce latent motility status indicators to model a cell's motility as a time-dependent characteristic.  We develop an MCMC algorithm to fit the model, which we apply to real experimental data from MDA-MB-231 cancer cells and NIH 3T3 fibroblasts.  Finally, I will discuss biological insights that we glean from the fitted models.

(This is a joint work with Saptarshi Chakraborty, Tian Lan, and Yiider Tseng)