Dynamics of atherosclerotic plaque formation, growth and regression. This project aims to provide a mathematical framework to interpret plaque growth. Many biological processes contribute to the growth of atherosclerotic plaques inside arteries. Lipoproteins enter the artery walls and stimulate tissues to signal to cells which duly respond so that fatty streaks form and grow into dangerous plaques that cause heart attacks or stroke. These processes are often nonlinear and operate on widely varyi ....Dynamics of atherosclerotic plaque formation, growth and regression. This project aims to provide a mathematical framework to interpret plaque growth. Many biological processes contribute to the growth of atherosclerotic plaques inside arteries. Lipoproteins enter the artery walls and stimulate tissues to signal to cells which duly respond so that fatty streaks form and grow into dangerous plaques that cause heart attacks or stroke. These processes are often nonlinear and operate on widely varying time scales. The project plans to use systems of ordinary differential equations, partial differential equations with non-standard boundary conditions, and bifurcation theory to find how nonlinear processes shape plaque growth. The expected results may demonstrate the importance of bifurcations, dynamics and nonlinear systems in plaque growth and provide new models to interpret biological data.Read moreRead less
Complex dynamical systems: inferring form and function of interacting biological systems. Often in biology a large number of simple parts interacting according to simple rules can result in behaviour that is rich and varied. This project aims to develop the mathematics of complex systems theory to describe how such collections of simple interacting parts can form large complicated structures, and to deduce what dynamical behaviour can result.
System identification of microstructure in the brain using magnetic resonance. Magnetic Resonance Imaging technologies will be exploited to probe the microstructure of the brain, using powerful Bayesian optimisation techniques and innovative uses of magnetic resonance. The project will in particular develop non-invasive imaging methods to quantify iron content in the brain, important for research on dementia and Alzheimer's disease.
System identification of microstructure in the brain using magnetic resonance. Magnetic Resonance Imaging technologies will be exploited to probe the microstructure of the brain, using powerful Bayesian optimisation techniques and innovative uses of magnetic resonance. The project will in particular develop non-invasive imaging methods to quantify iron content in the brain, important for research on dementia and Alzheimer's disease.