Inference-based Modelling in Population and Systems Biology

| Professor Mark Girolami | | Michael Stumpf | | Vincent Jansen |

Increasing amounts of biological data are being generated and collected which describe the change of biological systems over time. In systems biology, for instance, it is now normal practice to screen the interactions among a large number of molecules using automated techniques. To interpret such data we are more and more reliant on mathematical models. Such models summarise the way we think biological systems work. Together with experimental research collaborators we will explore how well these novel techniques work, and explore the new insights that we hope to get by using such techniques. The biological systems that we will study are: plankton in freshwater lakes, mechanisms by which bacteria cope with their environment, two different sets of interacting molecules, which transmit signals through cells, energy production during infection of barley by powdery mildew, and the ecosystem of algae, midges and fish in a lake in Iceland. These different biological systems will help us to fine tune the statistical techniques, suggest how to make the best use of biological data, and thus improve our understanding of how nature works. We will be recruiting three post-doctoral research assistants. One based at each of Glasgow, Imperial and Royal Holloway.

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