Bioinformatics and Systems Biology – (M.Sc.)

Bioinformatics has been an identifiable discipline for more than a decade, driven by the computational demands of high volumes of biological data. It incorporates both the development and application of algorithms to decipher biological relationships. Enormous success has been achieved, for example in defining homologous families of sequences at the DNA, RNA, and protein levels. However, our appreciation of function is changing rapidly as experimental analysis scales up to cellular and organismal viewpoints. At these levels, we are interested in the properties of a network of interacting components in a system, as well as the components themselves. The concepts or Systems Biology and Bioinformatics complement eachother, and both are addressed in this course. This combination reflects the current skills sought in academic and industrial (e.g. pharmaceutical) settings. An important feature is the extent to which computational biology is concerned with finding patterns in biological data, and generating hypotheses that feed back into experiments.

You will be based in the top-rated Faculty of Life Sciences at the University of Manchester. Teaching is delivered by more than 10 academic staff working in the fields of Bioinformatics, Genomics and Systems Biology, representing the breadth and depth of these areas across Faculties.

Course aims

The Bioinformatics course provides students with theoretical and practical knowledge of methods to analyse and interpret the data generated by modern biology. This involves the appreciation of biochemistry and molecular biology, together with the techniques of IT and computer science that will prepare students for multidisciplinary careers in research.

To achieve this there are three main objectives:

* Provide biological background to the data types of Genomics, Proteomics and Metabolomics.
* Develop the computational and analytical understanding necessary as a platform for processing biological data.
* Demonstrate applications and worked examples in the fields of Bioinformatics and System Biology, integrating with student involvement through project work.