Module

Course texts:

TBA

Submission

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines

Coursework should be submitted before 23:59 on the deadline day. Paper copies can be submitted via the Hub drop boxes up to 22.00  in the LTS Hub, and there will be a ‘late box’ in the Library for submissions between 22.00 and midnight.

If coursework is handed in after the deadline day or an agreed extension:

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.


Plagiarism

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be investigated. Possible consequences of plagiarism include deduction of marks anddisciplinary action, as detailed by UEA's Policy on Plagiarism and Collusion.

Module specific

To gain a critical understanding of the core techniques and approaches used in computational biology.

Transferable skills

• Critical assessment of the principles underpinning some of the most commonly used techniques and approaches used in computational biology.
• Competence in assessing and applying of learnt techniques and approaches.
• Improved ability to understand novel approaches that are constantly being introduced into computational biology.

Subject specific

Familiarity with core techniques and approaches commonly used in bioinformatics.

Total Hours: 24

Lectures: 12 hours; 1 hour per week; Content (with provisional weekly schedule)

1. Introduction (lecture 1)
2. Algorithms and Complexity (lecture 1-2): Termination, correctness and efficiency of algorithms, big O-notation, complexity of an algorithm.
3. Graph Theory (lecture 3-4): Basic terminology, Hamiltonian graphs, Kruskal's algorithm.
4. Clustering and trees (lecture 5-6): Hierarchical clustering algorithm, minimum/maximum and average linkage, introduction to phylogenetic trees.
5. Probability and Statistics (15-20): Counting, conditional probability, independence, mean, probability distributions.

Workshops: 20 hours; 2 workshops per week. Content (Note that the schedule below might change depends on whether there will be a reading week and if so when it will be). In general the workshops will deal with the material presented in the previous week.

1. None
2. Algorithms and complexity
3. Graph theory
4. Clustering and trees
5. Probability and statistics

Laboratory work: 0 hours

Course test (20%)

Examination (80%)

All pieces of coursework have a deadline for submission; indicated on the assignment sheet. For the group exercise, marks will be deducted for non-participation using the Yellow Card system. Students who fail to attend seminars will be reported to their Dean, and risk being deemed ineligible for assessment in the module.