Abstract: Mechanistic mathematical modelling is a powerful tool for understanding cell biological phenomena. One of the biggest challenges is the problem of scales: small scale events can result in large scale effects. In the two parts of my talk I will demonstrate the synergistic effects of mathematics and biology.
In the first part of the talk I will focus on a fundamental question in cell biology: What determines the size and position of a cell’s nucleus and how do they impact cell function and health, in particular in muscle cells? We use data-driven PDE and ODE models at different scales to test several modelling hypotheses. This allows identifying the most plausible model and draw conclusions about the underlying biological mechanisms.
In the second part of the talk showcases some projects in collective dynamics: I will discuss how to borrow techniques from topology and machine learning to analyse high-dimensional data from swarming models. Finally I will show how to use coarse-graining techniques to derive and analyse a model for pattern formation in bacteria.

us02web.zoom.us/j/4082603129