University of Newcastle upon Tyne

School of Mathematics and Statistics

Statistics Seminars 2004-2005

21 January 2005, M414, 2:00pm or 3:00pm

Dr Darren Wilkinson

Abstract

Modern Systems Biology is greatly concerned with using post-genomic experimental data sources in order to "fit" dynamic and predictive computer models of complex non-linear biological processes. If this is successful, scientists will be able to conduct "in silico" biological experiments that would be impossible to carry out "in vivo" and these could, in turn, transform our understanding of molecular biology. Unfortunately there are a great many obstacles in the way of this grand vision, and many are fundamentally statistical in nature. In this talk I will give an overview of my research interests in this area, starting with basic concepts of biological modelling, stochastic modelling and estimation ideas. We will then look at strategies for carrying out fully Bayesian inference for "small" biochemical networks, and outline the current state-of-the-art and limitations. Next we will move on to the problem of modelling and stochastic simulation of very large and complex biological systems, and finish by thinking about Bayesian calibration techniques that might be more appropriate in this more challenging context.

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