Developing algorithms and mathematical models for investigating the evolutionary dynamics of complex structural variants and epigenetic alterations in cancer

Project ID: 2228cd1340 (You will need this ID for your application)

Project Summary:

Cancer results from a complex evolutionary process in which different genetic and epigenetic alterations accumulate in the genome of cancer cells. To understand this process, several cancer studies have developed computational methods to reconstruct tumour phylogenetic trees by analysing the genetic alterations present in cancer cells using DNA sequencing data. However, epigenetic alterations and complex structural variants (SVs) have been mostly ignored in these evolutionary analyses despite their potential key role in cancer progression. A more comprehensive analysis of both genetic and epigenetic alterations is thus important to uncover novel mechanisms of cancer progression and related phenotypes (e.g., treatment resistance). This project thus has two key goals: (1) the development of algorithms for the identification of SVs and epigenetic alterations from DNA sequencing data, and (2) the design of computational, mathematical models to map SVs and epigenetic alterations on phylogenetic trees previously reconstructed using genetic alterations.

This project is highly cross disciplinary and it will span across three complementary academic disciplines: computer science, computational genomics, and evolutionary biology. In particular, the student will be embedded in the research teams of the TRACERx study, which is a leading international consortium composed of current leaders in cancer evolutionary analysis. The project will also be a training opportunity that will lead the candidate to develop the skills required to be part of the next generation of computational biologists with the required competences to address applications motivated by clinical and biological needs.

To achieve this, the student will receive training related to both theoretical and coding skills for the development of computational methods. Moreover, the student will benefit from the expertise of our wide network of collaborations within the UCL Cancer Institute. This project would suit candidates with a bioinformatics or computer-science background, with expertise in algorithm development and interest in studying cancer evolution.