Computational modelling
In parallel to the biology of urothelial cells, we have been developing a computational model of epithelial cell behaviour in collaboration with Dr Dawn Walker and Professor Rod Smallwood at Sheffield University. We are using a software agent-based approach to model the interactions between cells in an “in virtuo” culture environment. The purpose is to describe how emergent behaviour in a cell population arises as a consequence of cells interacting with each other and their environment. We have applied the computational model to examine wound repair in epithelial cell cultures and have begun to examine the implications of specific intracellular signalling mechanisms, such as autocrine EGFR signalling, on proliferation and differentiation.
Cell tracking using machine learning algorithms
A collaboration with Professor Steve Smith, School of Physics, Engineering and Technology, and Dr Dawn Walker.
Cell and population behaviours are inherently complex, but rudimentary to tissue generation - the cornerstone of tissue engineering. In our work, we apply cell tracking systems to time-lapse videos of cell cultures and then use 'white box' machine learning algorithms to characterise these cultures in terms of features such as average cell migration speed, in-contact angular velocity, cohesivity and average cell clump size. This offers the potential to provide a unique interpretable description of cell cultures that not only aids understanding but can also inform advanced modeling approaches.