Natural Sciences

Research in the biological sciences is increasingly dependent on large datasets such as those generated by DNA sequencing and microarrays. This is also true for diagnostics and medicine. Analysis of these datasets requires a range of skills and knowledge drawn from computer science, physical sciences and mathematics and statistics as well as biological sciences. Bioinformatics is the discipline that integrates algorithms and methods from these disciplines to model biological systems and infer patterns hidden in complex data.

You must have completed BIO2092 Genomics and Introductory Bioinformatics in order to take this module.

BIOM516 is an optional module for MSci Natural Sciences students only. You cannot take this module if you have already taken BIO3092 Bioinformatics.

This module’s main aim is to help to equip the next generation of biological scientists with a sufficient working knowledge of bioinformatics methods and concepts such that they can understand and critically evaluate the computational methods used in cutting-edge genomics and other biomedical sciences. Where possible and appropriate, the application of these bioinformatics methods will be illustrated with biological or biomedical examples from the recent peer-reviewed scientific literature. The module also aims to equip the biologist with sufficient comprehension of the subject to effectively communicate and collaborate with specialist bioinformaticians in handling/modelling/analysing large scale biological data and as such will  provide a foundation for those wishing to go on to postgraduate study in bioinformatics and related fields.

The skills you gain from lectures, practicals, readings and seminars will develop or enhance your employability. Transferable skills to other sectors include: problem solving (linking theory to practice, responding to novel and unfamiliar problems, data handling), time management (managing time effectively individually and within a group), collaboration (taking initiative and leading others, supporting others in their work), self and peer review (taking responsibility for own learning, using feedback from multiple sources) and audience awareness (presenting ideas effectively in multiple formats).

On successful completion of this module you should be able to:

Module Specific Skills and Knowledge

Discipline Specific Skills and Knowledge

Personal and Key Transferable / Employment Skills and Knowledge

Weeks 1 - 3: Basic tools used by bioinformaticians: The Unix/Linux, programming, and databases

Weeks 4 - 5: Methods for sequence analysis: alignment, assembly and functional prediction

Week 6: Density estimation for gene expression data

Week 7: Cluster analysis for gene expression data

Week 8: Classification analysis for gene expression data

Week 9: Regression analysis for gene expression data

Week 10: Systems biology - differential equations and difference equations

Workshop 1: Sequence analysis part I

Workshop 2: Sequence analysis part II

Workshop 3: Expression data cluster analysis

Workshop 4: Expression data classification analysis

Workshop 5:  Expression data regression analysis

Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e. a final overall module mark of less than 50%) you will be required to submit an essay. The mark given for a re-assessment taken as a result of referral will count for 100% of the final mark and will be capped at 50%.

Basic reading:

Zvelebil MJ and Baum JO, Understanding Bioinformatics, Garland Science, 2007 (Exeter library: 570.285 ZVE)

Agostini M, Practical Bioinformatics, Garland Science, 2012 (Exeter library: 572.86330285 AGO)

Duda RO, Hart PE and Stork DG, Pattern classification, Wiley-Interscience, 2000 (Exeter library: 001.534 DUD)

ELE: http://vle.exeter.ac.uk/

Web based and Electronic Resources:

Most of the concepts and methods are covered in these textbooks. However, we will also use examples from scientific journals such as Nature, Science, Genome Research, etc. and these materials will be provided via ELE.

Other Resources:

Reading list for this module: