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  Modelling and analysis of the dynamics of global gene expression for diagnosis, prognosis, molecular classification of diseases and new drug development

   Department of Automatic Control and Systems Engineering

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  Prof D Coca  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Microarray technology has become an important and powerful tool for high-throughput analysis of global gene expression and has applications in almost every field of biomedical research. Genome-wide association studies are increasingly used to identify the gene expression signature of a disease, understand the molecular mechanisms underlying the disease phenotype and identify new drug targets. However, most common bioinformatics approaches used to analyse gene expression are unable to handle time-course data, are not suitable for analyzing short, non-uniformly sampled time-series and do not fully explore the functional relationship between disease pathology and the dynamics and robustness of gene expression.

This project focuses on the development of control theoretical approaches for modelling, analysis and interpretation of dynamic gene expression data sets as well as for biomarker discovery.

Experimental data is provided by collaborators in Cardiovascular Science and the Centre for Stem Cell Biology.

Biological Sciences (4) Mathematics (25)

Funding Notes

This is a self-funded research project.
We require applicants to have either an undergraduate honours degree (1st) or MSc (Merit or Distinction) in a relevant science or engineering subject from a reputable institution.
Prospective candidates for this project should have either an undergraduate honours degree (2:1) or MSc (Merit or Distinction) in Control Engineering, Applied Mathematics, Physics or other related disciplines and programming skills.
Full details of how to apply can be found here:
Applicants can apply for a Scholarship from the University of Sheffield but should note that competition for these Scholarships is highly competitive: