Award details

MSc Applied Bioinformatics

Reference	BB/H020659/1
Principal Investigator / Supervisor	Dr Lee Larcombe
Co-Investigators / Co-Supervisors	Dr Simon Andrews, Professor Conrad Bessant, Dr Luca Bianco, Dr Nigel Carter, Dr Michael Cauchi, Dr Dan Crowther, Dr Joan Estany, Dr Andrew Garrow, Mrs Ghislaine Guigon, Dr Matthew Hall, Dr Julie Huxley Jones, Dr Chris Jones, Dr Khalku Karim, Professor Kathryn Lilley, Professor David Male, Dr Gareth Maslen, Dr Ramsay McFarlane, Dr Fady Mohareb, Dr Sarah Morgan, Dr Matt Page, Mr Philip Teale, Dr Christopher Walton, Dr James Warwicker, Dr Andrew White
Institution	Cranfield University
Department	Cranfield Health
Funding type	Skills
Value (£)	223,204
Status	Completed
Type	Training Grants
Start date	04/10/2010
End date	03/10/2013
Duration	36 months

Abstract

unavailable

Summary

Bioinformatics is about solving biological problems through the application of information technologies. Recent advances in bioanalytical platforms have resulted in the ability to acquire vast amounts of biologically-important data. Since the completion of large-scale genome sequencing projects both the volume and complexity of such data have further grown and we now have a framework on which to base what are known as the post-genomic technologies: transcriptomics, proteomics and metabolomics. Cutting-edge biology is focused increasingly on the elucidation of underlying biological mechanisms for which bioinformatic techniques are needed. These include advanced data analysis for biomarker discovery and data integration strategies required for systems biology. Developed with industry input, this bespoke MSc aims to produce graduates who are able to talk a common language with laboratory-based practitioners and play an increasingly important role in modern interdisciplinary biology. As such students will be trained in state-of-the-art bioinformatics tools and the analytical techniques for understanding and handling complex data sets, and also learn to programme in the major languages used in bioinformatics; R, Perl and Java. The course comprises five main compulsory elements: 1. Introductory streams: two streams designed to develop life science or IT students who join the course into a coherent cohort of bioinformatics students, able to communicate with a common language, and progress through the core application modules with a solid foundation of fundamental skills and knowledge. 2. A series of five core modules: Each module consists of one or two intensive weeks of teaching, with an average 50/50 split between lectures and hands-on computer work. Each module is typically followed by a study week in which the students tackle a significant piece of coursework related to the modules. These coursework assignments are all designed to typify real biological problems, which need to be solved using bioinformatics - examples include writing a software tool, extracting biologically relevant information from data, integrating data or modelling interactions or systems. 3. A software development group project: the group project is one of two integrative assessment points during the course designed to align the learning development with M-level experience and develop on key programming skills and application-specific informatics approaches form the core modules. Following initial lectures covering skills specific to the project, teams are formed to tackle challenging group projects. Each team is encouraged to work out their roles and management structure with guidance from the course tutors. 4. Integrating examination: undertaken by all students following the group project and immediately prior to beginning their individual research projects. This exam assesses the breadth of technical and conceptual knowledge and the student's ability to discuss this in the context of bioinformatics and wider associated fields. 5. An 18-Week Thesis Project Selected by the Student : In keeping with the aims of the MSc course, all projects must involve the application of bioinformatics approaches to solve a biological problem. Typically projects cover different applications (e.g. microarrays, proteomics, text mining, systems biology) and requiring different informatic skills (e.g .programming, statistics, databases). Projects are a major avenue for the involvement of our industrial partners, and an excellent opportunity for students to gain real-world experience. The course is specified to run with a maximum of 25 students and a minimum of 10, although it has run with fewer under exceptional circumstances. The optimum student number with current staff is 15. Please see the Case for Support and associated programme specifications for more details.

Committee	Not funded via Committee
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	X - not in an Initiative
Funding Scheme	Training Grant - Masters Training Account

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