In biological physics, the dynamics of cell populations can be modelled as a stochastic process similar to chemical reactions. In such models, individual cells typically choose stochastically when to divide and what specialised cell types to differentiate into. So far most stochastic models of stem cell fate choice exclude cell-cell interactions and feedback, which are likely important to regulate the emergent distribution of cell types. In biology, the mechanisms underlying differentiation of cells in the embryo are incompletely understood, and attempts at targeted differentiation of cells in culture suffer from low efficiency and insufficient control. Thus, a more quantitative understanding has the potential to contribute to improvements in healthcare, such as regenerative medicine.
A project could start by building on our preliminary efforts and extend these, for example to incorporate spatial interactions, different lineage hierarchies, or feedback circuits, and generate experimentally testable predictions. A successful candidate would have opportunity to interact with a network of active collaboration with biologists and mathematicians in Edinburgh and the UK.