Four year graduate degrees in genomic medicine and statistics
The University of Oxford offers a four year doctoral training programme in genomic medicine and statistics, training students to research in the methodologies required to understand the molecular basis of complex disease. The programme consists of a one year modular course (including formal teaching and two short research projects) followed by a three year doctoral research project, which can take place in any of the participating departments at the University. The course takes advantage of Oxford’s strengths in genetics, genomic medicine and statistics; disciplines that will set the medical research agenda of the 21st Century.
The Wellcome Trust Centre for Human Genetics (WTCHG), which will host the programme, has world-leading groups in statistics, bioinformatics, genomic analysis, protein structure and functional biology. United by a common interest in understanding the molecular basis of disease, researchers are affiliated to diverse departments, with interests ranging from susceptibility to infection, neurodegenerative disorders, cardiovascular disease, language development, mental illness, statistical genetics and statistical bioinformatics, and come from both clinical and pure science backgrounds. This combination of skills and interests, the ability to cross disciplines and to address old problems in new ways, has proved crucial to the scientific success of the WTCHG and provides a unique training opportunity. Students educated within the culture of the WTCHG are encouraged to develop cross-disciplinary interests, and to develop into scientists able to take new and unexpected approaches to old problems using the latest and emerging technologies. The WTCHG is already home to a number of such students and the doctoral programme builds on these, and other, interdepartmental links.
The doctoral programme is integrated with projects already in place at the WTCHG, identifying the susceptibility genes underlying common disease. Genetic and genomic studies pave the way to answering fundamental questions in epidemiology and disease aetiology: how and why populations differ in their spectrum of disease-variants; how these variants interact with environmental causes; how information about DNA sequence variants, gene expression and protein content relates to disease phenotype; how we can use this flood of new molecular information to arrive at improved definitions of disease that lend themselves to better diagnosis and treatment. Over the next few years it is likely that whole genome systems biology (including DNA copy number detection, gene expression, metabolite profiling and, eventually, whole genome resequencing of very large cohorts) will become routine. Consequently methods and research opportunities for dissecting complex disease will undergo a further revolution. This revolution is likely to be driven by scientists with strong quantitative skills aligned with a deep understanding of the underlying biology.
Members of the Mathematical Genetics Group at the Department of Statistics at the University of Oxford, at the forefront of developing and applying statistical tools for genomic analysis, are members of the WTCHG, including Professor Peter Donnelly FRS, who has been Centre Director since 2007. Members of the WTCHG have collaborated on several internationally important groundbreaking projects, including HapMap, the Wellcome Trust Case Control Consortium, 1,000 Genomes and the European Union MolPAGE programme.
Co-Directors:
Jonathan Flint: www.well.ox.ac.uk/flint/
Richard Mott: bioinformatics.well.ox.ac.uk/
Chris Holmes: mathgen.stats.ox.ac.uk/
Peter Donnelly: mathgen.stats.ox.ac.uk/
General Enquiries:
Penny Farrar: penny.farrar@well.ox.ac.uk
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