Course Information
COMP3353 Bioinformatics

COMP3353 Bioinformatics

2019-20
Instructor(s):Luo Ruibang
(Class A) No. of credit(s):6
Recommended Learning Hours:
Lecture: 28.5
Lab Session: 8.0
Tutorial: 2.5
Pre-requisite(s):COMP2119
Co-requisite(s):  
Mutually exclusive with:  
Remarks:

Course Learning Outcomes

1. [Bioinformatics Algorithms]
Be able to understand the important algorithms used in bioinformatics.
2. [Bioinformatics Tools]
Be able to understand the theoretical foundations and applications for several leading bioinformatics tools.
3. [Bioinformatics Database]
Be able to understand the function and organization of a few essential bioinformatics databases, and how do they support various types of bioinformatics analysis.
4. [Bioinformatics Analysis]
Be able to perform a few basic bioinformatics analyses using both existing and self-written tools.
5. [Bioinformatics Self-learning]
Be able to utilize the learnt knowledge to understand a bioinformatics new topic.
Mapping from Course Learning Outcomes to Programme Learning Outcomes
 PLO aPLO bPLO cPLO dPLO ePLO fPLO gPLO hPLO iPLO j
CLO 1TTT
CLO 2TTT
CLO 3TTT
CLO 4TTT
CLO 5TTT

T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to here.

Syllabus

Calendar Entry:
The goal of the course is for students to be grounded in basic bioinformatics concepts, algorithms, tools, and databases. Students will be leaving the course with hands-on bioinformatics analysis experience and empowered to conduct independent bioinformatics analyses. We will study: 1) algorithms, especially those for sequence alignment and assembly, which comprise the foundation of the rapid development of bioinformatics and DNA sequencing; 2) the leading bioinformatics tools for comparing and analyzing genomes starting from raw sequencing data; 3) the functions and organization of a few essential bioinformatics databases and learn how they support various types of bioinformatics analysis.

Detailed Description:

Bioinformatics Mapped to CLOs
Introduction to Bioinformatics1, 2, 3
Modern DNA sequencing1, 2, 3
Sequence alignment1, 2, 3, 4
Sequence assembly1, 2, 3, 4
Variant identification and annotation1, 2, 3, 4
Gene expression and regulation1, 2, 3, 4
Personal genome analysis and cancer genomics1, 2, 3, 4
Hot topics in bioinformatics and self-learning 1, 2, 3, 5
Advanced bioinformatics algorithms1, 2, 3, 4

Assessment:
Continuous Assessment: 70%
Written Examination: 30%

Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)