Department: Biological Sciences (School of)
Essex credit: 15
ECTS credit: 7.5
Available to year(s) of study:
Available to Study Abroad / Exchange Students: No Pre-requisites: BS221 OR BS222
|Module is taught during the following terms
Bioinformatics has evolved in recent years as a distinct discipline within the Biological Sciences to address the complexity of experimental data generated in the post-genomics era. The sheer volume of high-throughput data based on DNA sequence, RNA/gene expression and protein structure has necessitated the development of computational approaches for i) accessing and navigating database repositories and ii) analysing large datasets in order to obtain biologically-meaningful information (data-mining). These activities have traditionally been the realm of computational biologists, particularly in the development of computer software. However, as Bioinformatics becomes increasingly important in most areas of modern biology, there is a pressing need for biologists who do not have a computational/mathematical background to be able to understand and use the vast range of internet and software resources that are now available.
In addressing a recognised skills gap and in order to equip students from a Biomolecular background with valuable theoretical and practical skills, the Bioinformatics (BS312) module provides a broad-based curriculum that encompasses both traditional genomics together with RNA microarray and protein analysis methodologies. The emphasis of the module is on problem-based-learning; each topic is introduced by a lecture followed by a supervised session in the PC laboratory in which students follow detailed instructions that allow them to work through example datasets in order to understand and learn how to use and interpret commonly used methods. The sessions are supported by extensive documentation with guidance on further student-directed learning. No programming skills (computer language) are required; computational operations are all essentially 'point-and-click' and will use open-source software. Students will then be able to enhance their skills in their own private study.
To pass this module, students will need to be able to:
1. be competent in the use of general on-line utilities such as NCBI;
2. search intuitively for internet Bioinformatics resources including databases;
3. understand the principles and practical applications of commonly-used DNA sequence analysis algorithms;
4. demonstrate the ability to process and analyse gene expression microarray data downloaded from database repositories;
5. demonstrate competence in the use of different in silico methods for protein structure-function analysis;
6. demonstrate competence in pathway and network analysis methods;
7. have a good appreciation of the statistical methodologies upon which different Bioinformatics algorithms are based.
Learning & Teaching Methods
9 x 4hr sessions (36 hrs total); each session comprised of 1hr lecture, with a 3hr supervised PC class later in the week
4 sessions covering general utilities and DNA methods in weeks 2-5
5 sessions covering microarray and protein methods in weeks 7-11
(one session per week except for 'gap week' in week 6 when students complete coursework 1)
Student managed learning: 114 hrs
Total: 150 hrs
100 per cent Coursework Mark
Coursework 1 (covering DNA methods) weighted 40% (40 hrs in total)
Coursework 2 (covering RNA & protein methods) weighted 60% (60 hrs in total)
Both coursework elements will involve DAI including assessment of understanding of methodology; to be submitted in SPF.
Exam Duration and Period
- "Bioinformatics" by P H Dear, 2007 (Methods Express Series): Scion Publishing Ltd; ISBN: 978 1 904842 16 3.
"BIOS Instant Notes in Bioinformatics", 2nd Edition by C Hodgman, A French, D Westhead, 2009; Taylor and Francis; ISBN: 978 0 415 3949 9.
"Bioinformatics and Functional Genomics", 2nd Edition by J Pevsner, 2009; Wiley Scientific; ISBN: 978 0 470 08585 1