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  (BBSRC DTP) Understanding the evolution of gene regulatory networks through biophysical modelling and machine learning

   Faculty of Biology, Medicine and Health

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  Dr Mato Lagator, Prof M Rattray, Prof Tobias Galla  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

The ability to coordinate the expression of genes within a cell is at the heart of life. When and how much of a specific gene is turned into a protein is essential for organisms to respond to their environment and to manage resources. The need to carefully regulate genes has resulted in the evolution of gene regulatory networks – complex networks of interactions, where the protein product of one gene controls the expression of one or more other genes.  

While the structures of numerous gene regulatory networks have been studied intensively, we know very little about how those networks came to be. In particular, we do not know how the basic building blocks of gene regulatory networks determine network structures.  

In this project we will study this key question in evolutionary biology. You (together with your supervisors) will explore how the building blocks of gene regulatory networks in bacteria impact network structure. Bacterial networks consist of two components: short stretches of DNA situated upstream of the gene (called promoters) and proteins that bind to those promoters (transcription factors). The binding of transcription factors to a promoter is integrated into a signal, which determines the expression levels of the controlled gene. The basic mechanism of gene regulation is, therefore, the binding of transcription factor(s) to a promoter. The first goal of the project is to model these basic mechanisms using statistical thermodynamics in order to predict how mutations change TF-promoter interactions and, hence, how regulation evolves.  

Once we can model how mutations affect the regulation at individual promoters, you will explore how the structure of entire networks impacts their evolution. In other words, does the number of promoters, the number of TFs binding to each promoter and the regulatory relationship between promoter units impact how they evolve and change under mutational pressure.  

This interdisciplinary project will rely on machine learning and theoretical evolutionary modelling, with the option of backing up the theoretical findings with experiments on bacterial gene regulatory networks. Ultimately, understanding how network structure shapes network evolution will allow us to better predict the evolution of gene regulatory networks, and to study important processes like the emergence of multiple drug resistance in pathogenic bacteria and horizontal gene transfer.  

We are looking for a student with genuine interest in interdisciplinary work. The successful candidate can either be a student from physics, mathematics or computer science with a genuine interest in evolutionary biology, or have a biology background with profound interest in theoretical work. Strong programming skills are required, ideally in Python, C++ or Fortran. Excellent written and oral communication skills are essential. 


Applicants must have obtained or be about to obtain a First or Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science, engineering or technology.  

Before you Apply 

Applicants must make direct contact with preferred supervisors before applying. It is your responsibility to make arrangements to meet with potential supervisors, prior to submitting a formal online application.  

How To Apply 

To be considered for this project you MUST submit a formal online application form - full details on eligibility how to apply can be found on the BBSRC DTP website  

Your application form must be accompanied by a number of supporting documents by the advertised deadlines. Without all the required documents submitted at the time of application, your application will not be processed and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered. If you have any queries regarding making an application please contact our admissions team [Email Address Removed]  

Equality, Diversity and Inclusion  

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website  

Biological Sciences (4) Mathematics (25)

Funding Notes

Studentship funding is for 4 years. This scheme is open to both the UK and international applicants. We are only able to offer a limited number of studentships to applicants outside the UK. Therefore, full studentships will only be awarded to exceptional quality candidates, due to the competitive nature of this scheme.
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