Quantifying and controlling ecological cell systems
– Sara Hamis

Recent technological advances in molecular staining and microscopy have resulted in a multitude of spatio-temporal cell imaging data. These data hold rich information about how cells act and interact with each other, much of which current mathematical and computational methods are not able to extract.

In this talk, I will discuss ongoing work on developing methods and algorithms that probabilistically quantify cell actions and cell-to-cell interactions from imaging data. I will use simulated data to demonstrate that, given these quantifications, mathematical modelling can be used to predict and control system dynamics. Our methods build on spatial cumulant models (SCMs). SCMs are spatio-temporal population models that are formulated by differential equations and approximate the dynamics of two summary statistics generated by spatio-temporal point processes: first-order spatial cumulants (densities), and second-order spatial cumulants (spatial covariances).