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Bioinformatics

Module description

Research in the biological sciences is increasingly dependent on large datasets such as those generated by DNA sequencing. This is also true for medical diagnosis and prognosis. 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.

This module would benefit from a prior knowledge of Linux, bash and R. However, tuition will be given in the workshops for students who are unfamiliar with these programming languages.

Module aims - intentions of the module

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 and 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.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

• 1. Perform basic analyses on large-scale biological data
• 2. Select proper data analysis tools to analyse biological data

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

• 3. Analyse biological data in a systematic way including data uploading, data organisation, data pre-processing, data analysis, results summary and data analysis reporting

ILO: Personal and key skills

On successfully completing the module you will be able to...

• 4. Communicate effectively arguments, evidence and conclusions using written means in a manner appropriate to the intended audience
• 5. Analyse and evaluate data with limited guidance

Syllabus plan

• Basic tools used by bioinformaticians: R programming
• Methods for genomics: alignment, assembly, variant calling
• Methods for phylogenetics: phylogenetic tools and algorithms
• Methods for population genetic analysis: recombination, linkage, etc.

Workshops to cover: Linux/OpenStack, sequence alignment, variant calling, phylogenetics, and population genetics methods.

Accessibility statement:

As part of this module you will undertake sessions in the computing laboratory (of up to 80 students) that are up to 3 hrs in duration. Breaks are possible and students are able to leave the laboratory for short periods. In addition, as part of this module you will attend a single seminar (in groups of up to 20 students and a lecturer) to discuss a research paper that has been shared with you the previous week. Student participation and discussion is expected within these seminars.

Learning activities and teaching methods (given in hours of study time)

Details of learning activities and teaching methods

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

Details of re-assessment (where required by referral or deferral)

Re-assessment notes

Deferral – if you miss an assessment for certificated reasons that are approved by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. If deferred, the format and timing of the re-assessment for each of the summative assessments is detailed in the table above ('Details of re-assessment'). The mark given for a deferred assessment 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 (i.e. a final overall module mark of less than 40%) and the module cannot be condoned, you will be required to complete a re-assessment for each of the failed components on the module. The format and timing of the re-assessment for each of the summative assessments is detailed in the table above ('Details of re-assessment'). If you pass the module following re-assessment, your module mark will be capped at 40%. 

Indicative learning resources - Basic reading

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.

• 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)

Indicative learning resources - Web based and electronic resources

• ELE page:
  

Key words search

Bioinformatics, next-generation sequencing