Bioinformatics MPhil – (M.Phil.)

The MPhil is a one-year research degree where students get the opportunity to study a specific research project. The MPhil degree can act as a stand-alone degree for applicants who would like to gain experience in a specific area, or can be linked to a PhD programme. Rather than register on a direct entry 3 or 4 year PhD, some postgraduates may first register on a one-year MPhil programme. Subsequently students may then wish to transfer on to a full PhD programme with a further 2 or 3 years of study.

The Faculty of Life Sciences is home to one of the country's leading groups of bioinformaticians and functional genomics practitioners, with the largest concentration of bioinformaticians in any UK higher education institute. Recent recruitment has expanded the portfolio of research topics, developing excellence in systems biology, molecular evolution and analysis of noncoding gene function. This highly collaborative and multidisciplinary grouping now covers the breadth of postgenomics and bioinformatics, and offers a unique environment for modern bioscience research.

The Bioinformatics and Functional Genomics grouping seeks to study and understand biological function through a mixture of `wet' and `dry' approaches, from molecular building blocks to genome and systems-wide features, which they aim to model and predict. This `predictive' biology has been brought about by a number of factors, including the growing numbers of gene/protein sequences in the databases and a similar expansion in the molecular structures of proteins available to study. The large number of completed genome sequences has also spawned post-genomic technologies, which aim to characterise gene products (transcriptome, proteome) and the molecules they manipulate (metabolome), as dynamic, functional entities within the cell. This group develops and applies computational approaches to enable these technologies, as well as carrying them out. This can take the form of classic bioinformatics, designing and developing databases such as PRINTS, comparing gene, protein and/or genome sequences and their evolution, and modelling and predicting protein structures. Equally, tools and technology are required for these post-genomic analyses, handling and analysing microarray data, building proteome repositories and search tools, and modelling and predicting metabolic pathways.