The 3’ Untranslated Region (UTR) of a transcript presents a complex set of binding sites that are used to regulate both transcript stability and downstream protein translation. These include target sites for microRNAs (miRNAs) as well as a multitude of RNA binding proteins. These act together in tightly coordinated patterns in order to control protein expression. Many of these systems are perturbed in tumours, resulting in aberrant protein levels. A detailed understanding of how 3’ UTRs interact with this regulatory machinery is therefore critical to our understanding of how post-transcriptional events control tumour growth and maintenance.
The goal of this PhD is to use Machine Learning to investigate regulatory patterns within the 3’ UTR, and to ask how they help coordinate genome-wide expression programmes. The project will involve working closely with bench-scientists within the RNA and Translation Control in Cancer Group (Martin Bushell), who are using high throughput approaches to profile the regulatory interactions that occur at the 3’ UTR. It will therefore involve building multi-omics models that integrate genome-wide deep sequencing and protein mass spectrometry datasets with single cell sequencing.
The studentship will be based in the Computational Biology Group (led by Crispin Miller) and will have access to substantial computing hardware, including GPU-accelerated machine learning systems. While detailed knowledge of cell biology would be advantageous, it is not a pre-requisite, and this project is particularly well-suited to enthusiastic scientists from numerical disciplines who are interested in applying their computational skills to fundamental questions about cell biology, and to ask how these advance our understanding of tumour biology.
The Cancer Research UK Beatson Institute in Glasgow is one of the world-leading centres for cancer research. The Institute provides an outstanding research environment, underpinned by state-of-the-art core services and advanced technologies with special emphasis on imaging, metabolomics and in vivo models of cancer.
To apply, please click on the ’Visit Website’ button, which will take you to the Beatson Institute website where you should fill in the application form. Please do not email your CV.