CS4220 Knowledge Discovery Methods in Bioinformatics
Instructor: Limsoon Wong & Niranjan Nagarajan / 2013/2014 Semester 2 / IVLE

• 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

  Course Plan

  • Unit 1: Essence of Biostatistics
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  • Unit 2: Essence of Data Mining
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  • Unit 3: Gene Expression Profile Analysis
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  • Unit 4: Proteomic Profile Analysis
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  • Unit 5: Biological Network
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  • Unit 6: Protein Complex Prediction
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  • Unit 7: Protein Function Prediction
    Offered only if there is time.

    
    
    
    

  • Unit 8: Pathway Perturbations in a Disease Context
    Slides

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  Contact: Limsoon Wong / Last updated 23 March 2014