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Curricular information is subject to change
This will teach non-biologists a lot of biology by forcing exposure to biological data. It will teach biologists a lot of computer application issues (CGI, relational database model, mysql, html, and others) . It will give students introductory specialist knowledge in a number of applied bioinformatics areas. It will expose students to the extent of complex and difficult-to-structure observational data in modern biology and the markedly heuristic approaches favoured in biology.
Lectures will cover techniques and methods for dealing with the following kinds of data:
- database structure and manipulation.
- genomic data (compiling, analysing and annotating DNA sequencing data).
- clinical bioinformatics (SNPs, alleles, haplotypes)
- interactome data (proteomics data, protein complexes, protein identification).
- chemical information (combinatorial libraries, SDF, SMILES, SMARTS, fingerprints).
- protein structural data (PDB, homology modelling, active site determination).
�Hands on� experience in the tutorials will take students through the basic steps needed to build a program that retrieves and stores web-based biological data. After the three days of tutorials students will be able to start from an unformatted computer hard drive and end with a functional, searchable database of biologically relevant information.
| Student Effort Type | Hours |
|---|---|
| Lectures | 15 |
| Tutorial | 15 |
| Autonomous Student Learning | 70 |
| Total | 100 |
BSc(Hons) in Biology or Computer Science
Learning Recommendations:Python Programming for Computational Biologists (COMP50050)
| Description | % of Final Grade | Timing |
|---|---|---|
| Continuous Assessment: Self assessment sheets scored and signed off by supervisors | 100 |
Varies over the Trimester |
Compensation
This module is not passable by compensation
Resit Opportunities
In-semester assessment
Remediation
If you fail this module you may repeat, resit or substitute where permissible