PhD studentship in Bayesian Methods in Bioinformatics, Warwick Systems Biology Centre

Maintenance grant of £12 283 pa plus academic fees
Duration: 3 years

You should have a good first degree in a relevant quantitative fieldsuch as theoretical physics, engineering, applied mathematics,statistics etc and a strong interest in molecular biology.

The overall goal of this multidisciplinary project is to combinefunctional genomics and computational modelling into a novelintegrative systems approach aimed at identifying key components ofthe regulatory networks involved in cell physiology. The project aimsto develop a computational framework based on a probabilisticmodelling technique (Bayesian state-space models), within the contextof real-world scientific problems.

In this project we propose innovative directions to significantlyextend this network modelling approach, incorporating into the modellearning and inference process nonlinearities that reflect theunderlying biological mechanisms and prior knowledge in the form ofknown connections. In the first phase of this research, the focus willbe to develop the computational framework to effectively model thetemporal gene expression profiles of a subset of genes derived fromdifferential expression profiling. The second phase of this work willinvolve a tightly coupled iterative cycle of computational modellingand independent experimental validation of model predictions usingover-expression and gene silencing experiments by collaboratinggroups. The new computational tools will be developed in the contextof real-world scientific problems: the understanding of stressresponse in the model plant species Arabidopsis at a molecular leveland metabolic regulation in the bacteria Streptomyces, major producersof antibiotics and bioactive products. These are well-defined systemsof biological interest that can be easily manipulated experimentallyand for which genomic information and the necessary investigativetools are available.

Warwick Systems Biology Centre has a thriving research andpostgraduate training programme at the interface of the life sciencesand the mathematical and physical sciences.

1. Beal, M.J., Falciani, F., Ghahramani, Z., Rangel C. and Wild,D.L. A Bayesian approach to reconstructing genetic regulatory networkswith hidden factors. Bioinformatics, 21: 349-356 (2005).
2. Rangel, C., Angus, J., Ghahramani, Z., Lioumi, M., Sotheran, E.,A., Gaiba, A.,.Wild, D.L. and Falciani, F. Modeling T-cell activationusing gene expression profiling and state space models.Bioinformatics, 20(9):1361-1372 (2004).
3. Rangel C., Angus J., Ghahramani Z. and Wild D.L. Modelinggenetic regulatory networks using gene expression profiling and statespace models. In Husmeier, D., Roberts, S. and Dybowski, R. (Eds.) ,Applications of Probabilistic Modelling in Medical Informatics andBioinformatics. Springer Verlag, (2004), pp. 269-293.

Details of requirements can be found here:
http://www2.warwick.ac.uk/study/postgraduate/apply/

Applicants should apply online at:
http://www2.warwick.ac.uk/study/postgraduate/apply/process/

Informal enquiries: Prof. David Wild (d.l.wild@warwick.ac.uk)
Closing date: Applications accepted all year round, start date asap
Please quote job vacancy reference number WSB01-017.

The closing date for applications is 31 January 2007.