The programme will provide students of mathematical sciences with the necessary skills for successful research in statistical aspects of bioinformatics. We aim to produce graduates with the flexibility to adapt to differing future problems in the subject. On completion of the course students should be able to understand statistical concepts in the analysis of bioinformatics data, implement algorithms, construct data models, design databases, use commonly available software for the analysis of biomolecular sequences and structures and interpret the results. Finally, they should have demonstrated the ability to carry out a significant statistical bioinformatics research project, and be able to give oral and written reports on the results. It is expected that projects should show potential for publication in the peer reviewed literature.
12 months full time
The School of Mathematics at the University of Leeds, which comprises the departments of Statistics, Pure Mathematics and Applied Mathematics, is one of the largest and most active in the country. The School has over eighty members of staff, including about twenty-five professors. The School of Mathematics has recently established a Centre of Statistical Bioinformatics and has appointed Professor Wally Gilks as Director. This Centre, in collaboration with existing research groups from around the University, provides a forum for problem-sharing, development of new methods, and promoting the role of statistics in the rapidly developing field of bioinformatics.
What you study
* An introduction to molecular biology
* Bioinformatics of DNA, RNA and protein sequence, structure, function and evolution
* Statistical models and methods used widely in bioinformatics, for example: hidden Markov models; generalized linear models; analysis of variance; multivariate analysis; Bayesian methods; MCMC
* Use of statistical methods to solve bioinformatic problems
* Statistical analysis of gene expression data, for example from microarray and mass spectrometry experiments
* Statistical genetics
How you study
-The course is taught by a mixture of lectures, tutorials, and computer-based experience.
-You will need to spend time in guided private study, involving reading, computing and internet-based activity.
-You must complete an individual, supervised, research project to investigate a topical bioinformatic problem from a statistical perspective. The project will involve preparation of a dissertation, worth half of the total course credits.
-You will be assigned a tutor who will monitor your progress and provide you feedback and support.