CS4220 Knowledge Discovery Methods in Bioinformatics
Limsoon Wong &
Niranjan Nagarajan /
2012/2013 Semester 2 /
- Lecture and tutorial are held every Thursday @ 2-5pm in SR @ LT19.
- Present-day biomedical researchers are confronted by vast amounts of
data from genome sequencing, microscopy, high-throughput analytical
techniques for DNA, RNA, and proteins, and a host of other new experimental
technologies. Coupled with the advances in computing power, this flow of
information should enable scientists to model and understand biological
systems in novel ways.
The goals of CS4220 (Knowledge Discovery Methods in Bioinformatics) are:
(1) expose students to knowledge discovery techniques,
(2) enhance students' flexible and logical problem solving skills,
(3) develop students' understanding of bioinformatics and issues in
analysis of real-life high-throughput biological data.
To achieve these goals, we do a series of in-depth studies and hands-on
projects on topics such as gene expression profile analysis,
epistatic interaction detection, protein family recognition, etc.
At the end of the course, students will be able to identify the relevant
techniques for different biological data to uncover new information,
as well as be confident in formulating and validating hypothesis underlying
observations from biological data.
Course briefing slides
Unit 1: Essence of Biostatistics
Unit 2: Essence of Data Mining
Unit 3: Gene Expression Profile Analysis
Unit 4: Proteomic Profile Analysis
Unit 5: Biological Network
Unit 6: Protein Complex Prediction
Unit 7: Protein Function Prediction
- Unit 8: Pathway Perturbations in a Disease Context
Contact: Limsoon Wong /
Last updated 8 January 2013