Mathematical modelling of tissue self-assembly

How tissues self-assemble, and how different cell types are established and maintained in such tissues, are fundamental questions in developmental biology with profound implications for tissue engineering and regeneration strategies. While the signalling molecules involved are increasingly well characterised, we still lack a mechanistic understanding of the contribution and timing of short- vs long-range signalling, and their effect on cell proliferation and adhesion. Alongside experimental studies, mathematical models help challenge and refine our understanding of these processes.

Building on recent work by myself and others (Fletcher et al, 2017; Osborne et al, 2017), this project will develop new models of tissue growth and patterning, incorporating multiple signalling mechanisms (autocrine, juxtacrine, paracrine). Detailed analysis will identify how different modes of tissue self-assembly emerge from combinations of these mechanisms in time and space. This work will be applied to the hypothalamus, which regulates core body processes that are essential for survival. Informed by recent findings by Prof. Marysia Placzek (based in the Department of Biomedical Science) on hypothalamus self-assembly (Robins et al, 2013; Fu et al, 2017), and in vitro organoid data that recapitulates development in vivo. Models will be developed to understand whether and how local versus longer-range signalling events underlie hypothalamic cellular homeostasis, cellular architecture and self-assembly.

This interdisciplinary project would involve the development and analysis of ordinary and partial differential equation models, and/or cell-based models, of tissue growth and patterning. It would suit a student with undergraduate training in the physical sciences and an appreciation of the importance of mathematical modelling in the life sciences.

Science Graduate School:
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