Bioinformatics

Entry requirements

We require applicants to hold, or be about to obtain, an Upper Second class Honours degree, or the equivalent qualification gained outside the UK, in a related subject area for entry to a PhD programme. A Lower Second class Honours degree may be considered if applicants also hold a Master's degree with a Merit classification.

Months of entry

January, April, September

Course content

Our PhD/MPhil Bioinformatics programme enables you to undertake a research project that offers training in state-of-the-art computational approaches to study an aspect of biological and/or biomedical science.

Manchester is a leading centre for bioinformatics and computational biology, with one of the largest concentrations of academic groups in any UK higher education institute.

Biology is increasingly becoming a more digital science that generates large volumes of complex data, requiring allied informatics skills to process, analyse and store the information generated, leading to better interpretation of biological function, and potentially novel predictions. This can be used in both biology and clinical settings, for prediction of gene function in biological processes as well as in diagnostics and prognostics linked to disease.

This growth in the area has, in the main, been driven by the expansion of genomic and post-genomic technologies (e.g. next generation sequencing and allied 'omics) that generate high volumes of sequence and gene expression information, for example for the human 100,000 genomes project.

Incresingly, this can also involve spatial and temporal information such as imaging data, as well as recent developments in protein structure prediction. By integrating such data sources including evolutionary, environmental, text-mining and more, new understanding and discoveries can be made which place bioinformatics at the core of modern bioscience research.

We cover the full range of skills and expertise across an exciting portfolio of research topics, ranging from sequence analysis of nucleotides and proteins, through to integrated systems biology and mathematical modelling and machine learning.

We analyse data and generate tools linked to topics such as noncoding gene function, transcriptional networks, systems biology of cancer, antimicrobial resistance, protein folding and aggregation, quantitative proteomics and metabolomics in organisms ranging from viruses, microbes and model organisms to man. This often involves informatics approaches to help close the genotype-phenotype gap - i.e. why does varying at the genetic level lead to a particular change in phenotype, such as genetic disease.

Bioinformatics postgraduate research students also often form part of highly collaborative and multidisciplinary teams tackling major problems in biomedical science, offering opportunities to work closely with experimental colleagues in a mutually supportive environment.