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Module Detailed Information for [CS4220]
Academic Year : 2018/2019 Semester : 2
Correct as at 21 Feb 2019 05:00

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Module Information
Module Code :
Module Title : Knowledge Discovery Methods in Bioinformatics
Module Description : The advent of high throughput technologies (e.g, DNA chips, microarray, etc), biologists are being overloaded with lots of information (e.g., gene expression data). To be able to make sense out of these data, there is a need to have a systematic way to analyse them. This course is introduced to provide students with knowledge of techniques that can be used to analyse biological data to enable them to discover new knowledge. At the end of the course, students will be able to identify the relevant techniques for different biological data to uncover new information. Topics include: Clustering analysis, classification, association rule mining; support vector machines; Hidden Markov Models.
Module Examinable : -
Exam Date : 29-04-2019 PM
Modular Credits : 4
Pre-requisite : CS2220 or LSM2104
Preclusion : Nil
Module Workload (A-B-C-D-E)* : 2-1-0-4-3
Remarks : Nil
* A: no. of lecture hours per week
B: no. of tutorial hours per week
C: no. of laboratory hours per week
D: no. of hours for projects, assignments, fieldwork etc per week
E: no. of hours for preparatory work by a student per week

Lecture Time Table
Class TypeWeek TypeWeek DayStartEndRoom

Tutorial Time Table
Attention: The tutorial timetables could be updated from time to time. Students are advised to check regularly for the latest update on the change of tutorial timing.
No Tutorial Class or to be announced. Please check with the department offering this module.

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