Mathematics of Biological Systems: Modelling, Data & Analysis

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To predict and preventing diseases such as cancer, diabetes and AIDS we need to do more than identify the components that make up the machinery of cells and tissues. We must also understand how these components interact to produce normal and pathological behaviour. Since the interactions between genes, transcripts, proteins, metabolites and cells are complex and dynamics, mathematical modelling and analysis will be needed for their understanding. Moreover, there is a rapidly growing number of powerful technologies that probe gene expression and the abundance and spatial distribution of metabolites and proteins. These produce huge amounts of data and require the development of new mathematical and statistical methods. This and the associated experimental design problems pose considerable mathematical and statistical challenges.This work will be developed in a number of biological areas chosen with the expectation that results obtained for these are likely to be generalisable. These include circadian clocks, photoperiodism, immunology of T cells, plant development (flowering), the control of apoptosis (cell suicide) and replication, and bacterial signalling. The research involves extensive collaboration with experimental groups and will be carried out in a multidisciplinary context involving mathematical and physical scientists as well as biologists and clinicians.