Aims and Fit of Module
The biological and computational modules delivered in the first two years of BSc Bioinformatics program will be integrated in this module under bioinformatics framework to address various issues related biological databases, sequence comparison, phylogenetics, and other sequence related analysis. Lab sessions in BIO211 emphasise basic programming and hands-on skills to work with biological sequences, i.e., DNA, RNA and proteins.
In BIO211, biological databases, sequence comparison, phylogenetics, and other sequence related analysis are delivered together with recent developments. The students are expected to:
1. Get familiar with biological databases, issues in sequence analysis
2. Understand the mathematical formulation of sequence comparison and phylogenetic analysis
3. To be able to use computer science approach and bioinformatics software to solve practical problems related to sequence comparison, phylogenetics.
A Demonstrate a systematic knowledge in biological databases, sequence comparison, phylogenetics, and other sequence related analysis, and to provide the students with hands-on
B Understand most classic content within the domain of biological databases, sequence comparison, phylogenetics, and other sequence related analysis.
C Analyse datasets of relevance to biological databases, sequence comparison, phylogenetics for future research projects.
D Demonstrate information literacy skills in the discovery, evaluation and acquisition of data from public resources.
E Enable the students to choose an appropriate tool among several computational approaches.
F Have a comprehensive understanding of various biological databases from both computational and biological perspective.
G Familiarity to implement the classic sequence analysis algorithms by hand- calculation or on by computer programming.
H Use popular main-stream bioinformatics resources to address well-defined problems such as phylogenetic analysis, etc.
Method of teaching and learning
1. Didactic component - the core of the teaching is lecture-based with Q/A and feedback.
2. Self-learning component - students are encouraged to read around the subject materials.
3. Comprehension/review exercise - two continuous assessments, following supervised discussion and Q/A sessions in the seminars.
4. Case studies will be supplied to help students place the course material in context.
5. Working in computer lab with bioinformatics tools to solve practical problems.
There are totally 50 hours public time, which is roughly divided into 13 weeks. And in each week, there should 2 hour lecture, 1 hour tutorial and 1 hour computer lab session.