Reverse engineering and design of natural and synthetic biological systems

Chris Barnes (UCL)

Friday 1st February, 2013 15:00-16:00 Maths 204


Mathematical modelling has become an essential tool to aid the understanding of cellular behaviour. A major challenge is to relate experimental observations to the complex network of biochemical reactions underlying the system. This process -- which I shall refer to as {\em reverse-engineering} -- is particularly difficult for biological systems because of their complexity, stochasticity, spatial localisation and plasticity. Additionally the observational data often constitutes partial observations of the system which makes many mathematical models consistent with the observations.

Bayesian statistics provides powerful methods for handling uncertainty and one particular tool that is of particular use in biology is model selection. Given a set of competing models, Bayesian model selection allows one to infer the most probable model, or models, that give rise to the observations. Here I shall present one example of how Bayesian model selection was used to provide evidence for an intermediate state in tumor-propagating cells in multiple myeloma patients.

In the second part of my talk I will show how the same reverse engineering methods can be applied to the problem of how to design systems. This enables the use of the Bayesian framework for the design of synthetic biological systems and the investigation of the design principles of biochemical networks. Specifically, given a specified set of input conditions and a desired set of output conditions, in principle, the topology of the system (the set of reactions) and the kinetic parameters can be inferred in a technique analogous to reverse engineering. There are many nice properties of this framework, one of which is the ability to compare different models based on their robustness, by which we mean those designs that will function over a wide range of biochemical parameters. I will demonstrate this through examples of biochemical adaptation and the design of a stochastic toggle switch.

Add to your calendar

Download event information as iCalendar file (only this event)