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3.2.6    Bachelor of Computing in Computational Biology

  Home / NUS Bulletin AY2017/18 / School of Computing / Undergraduate Education / Degree Requirements / Bachelor of Computing in Computational Biology

Overview

The main objective of this programme is to provide a multidisciplinary education, to produce graduates who would be equally at ease with algorithm design and mathematical and statistical analysis as they would be with biochemistry, biology/genetics, and wet-lab know-how. Besides an opportunity to pursue a career in IT, graduates from the programme will also be equipped for a career in the fast-paced pharmaceutical, biomedical or biotechnology industries. This will help meet the demand of the local market for talents with such skill sets. Moreover, the breadth of instructions will pave the way for good students to pursue graduate studies in Bioinformatics.

Programme Structure

The programme is structured such that both Computing and Faculty of Science students share a common core multidisciplinary curriculum (lower division) in their first two years of study.

The lower division embraces a fundamental body of knowledge in which a computational biologist should be proficient. This body of knowledge consists of the following:

  • Discrete mathematics and combinatorics, i.e., logic, sets, graphs, counting techniques, etc.;
  • Probability and statistics, i.e., sample spaces, random variables, conditioning, distributions, design of experiments, significance tests, statistical inference, etc.;
  • Algorithm design and proficiency in some current programming language, i.e., combinatorial algorithms, algorithmic paradigms, analysis and design, working knowledge of current languages (for example, C, C++, Java) and experience in writing actual nontrivial code;
  • Organic chemistry and biochemistry;
  • Biology and genetics, including a moderate amount of wet-lab experience.

The upper division specialised track trains students in algorithmic design to facilitate the design of computationally efficient software and tools in both centralised and networking environments. Students in this track will pick up skills in software engineering, networking and advanced techniques in algorithmic design. Students may also take modules from the Computational Biology elective list.

Degree Requirements

The Computational Biology programme degree requires at least 160 MCs. Modules are classified as follows (note that every module can only be counted towards satisfying exactly one requirement):

Students will be required to satisfy 12 MCs of industrial experience (mandatory requirement) by doing:

  1. A 6-month internship through CP3880 Advanced Technology Attachment Programme (12 MCs)
  2. Two 3-month internships through CP3200 Internship (6 MCs) and CP3202 Internship II (6 MCs). With two internships, the student will be able to experience work in two distinct types of organizations, such as a start-up and a MNC, or in two different industries.
  3. IS4010 Industry Internship Programme (12 MCs) from the IS department.
  4. A 3-month internship through CP3200 Internship (6 MCs) and an Industry Course (4 MCs)1. The remaining 2 MCs may be satisfied using Unrestricted Electives.
  5. iLead or NOC 2.
  6. Other forms of industry experience approved by the Department of Computer Science.
  1. PROGRAMME REQUIREMENTS (Total of 124 MCs)

Common Essentials

CS1010   Programming Methodology3
CS1020   Data Structures and Algorithms I4
CS2010   Data Structures and Algorithms II4
CS2100   Computer Organisation
CS2102   Database Systems
CS2103T  Software Engineering5
ES2660   Communicating in the Information Age

Major Requirements
Level-1000 
CM1401  Chemistry for Life Sciences
CS1231   Discrete Structures
LSM1102   Molecular Genetics
LSM1106   Molecular Cell Biology
MA1101R   Linear Algebra I
MA1521   Calculus for Computing

Level-2000 
CS2220   Introduction to Computational Biology
CS2101   Effective Communication for Computing Professionals
ES2660  Communicating in the Information Age

Either
LSM2211   Metabolism and Regulation
or
LSM2232   Genes and Genomes
or
LSM2233   Cell Biology

LSM2241    Introductory Bioinformatics
ST2334   Probability and Statistics6

Level-3000 
CS3230   Design & Analysis of Algorithms
LSM3241   Bioinformatics and Biocomputing

Either
CS3225   Combinatorial Methods in Bioinformatics
or
MA3259   Mathematical Methods in Genomics

Minimum of 12 MCs from the following list7:

Either
CS3225   Combinatorial Methods in Bioinformatics
or
MA3259   Mathematical Methods in Genomics
CS3240   Interaction Design
CS3241   Computer Graphics
CS3243   Introduction to Artificial Intelligence
CS3244   Machine Learning

Level-4000 

CS4220   Knowledge Discovery Methods in Bioinformatics
LSM4241   Functional Genomics
Industrial Experience Requirement (12 MCs) 8

Complete 8 MCs by taking modules from CB Elective Course List

Computational Biology (CB) Elective Course List 9 

CS4221   Database Applications Design and Tuning
CS4231   Parallel and Distributed Algorithms
CS4234   Optimisation Algorithms
CS4235   Computational Geometry
CS4237   Systems Modelling and Simulation
CS4243   Computer Vision and Pattern Recognition
CS4244   Knowledge-Based Systems
CS4248   Natural Language Processing
CS5228   Knowledge Discovery and Data Mining
CS5234   Combinatorial & Graph Algorithms
CS5238   Advanced Combinatorial Methods in Bioinformatics
CS5340   Uncertainty Modelling in Artificial Intelligence

  1. UNIVERSITY LEVEL REQUIREMENTS

As specified in Section 3.2.1.

  1. UNRESTRICTED ELECTIVES

As specified in Section 3.2.1.

NUS Overseas Colleges (NOC) (Computational Biology)

Students who attend 1-year NUS Overseas Colleges (NOC) may:

  1. Count TR3201 Entrepreneurship Practicum (8 MCs) towards computational biology electives.
  2. Count TR3202 Start-up Internship Programme (12 MCs) towards Industrial Experience Requirement.
  3. Count TR3203E Start-up Case Study and Analysis (8 MCs) towards level-3000 electives.  Students should work on a computational biology-related project to take TR3203E.  Otherwise, students should take TR3203 instead (which counts towards Unrestricted Electives).

Students who attend 6-month NUS Overseas Colleges (NOC) may:

  1. Count TR3202 Start-up Internship Programme (12 MCs) towards Industrial Experience Requirement.
  2. Count TR3203E Start-up Case Study and Analysis (8 MCs) towards one level-3000 elective (4 MCs).  The remaining 4 MCs counts towards Unrestricted Electives.  Students should work on a computational biology-related project to take TR3203E.  Otherwise, students should take TR3203 instead (which counts 8 MCs towards Unrestricted Electives).
University Scholars Programme (Computational Biology)

Students in the University Scholars Programme (USP) who choose the Bachelor of Computing (Computational Biology) major will take the Computational Biology programme, but with the following variations:

  1. They will read GER1000 Quantitative Reasoning (4 MCs) as compulsory module for the University Level Requirements (ULR). The remaining 16 MCs in ULR are replaced by the 3 USP Inquiry Modules and 1 USP Foundation module ( i.e. University Scholars Seminar).
  2. They will not be required to read CS2101 Effective Communication for Computing Professionals.  It is replaced by USP Foundation module: Writing and Critical Thinking.
  3. With the special permission from the UROP coordinator and Computational Biology Programme Coordinator, they will read CP3208/CP3209 Undergraduate Research in Computing I/II with a project on computational biology as independent study modules (ISMs), which will be counted as 2 USP Inquiry modules in Sciences and Technologies Basket.
  4. They will further complete 3 more USP Inquiry modules (for a total of 8 USP Inquiry modules, including CP3208 and CP3209) and the USP Reflection module (the Senior Seminar).  They will have no MCs under the Unrestricted Electives.
Table 1: Summary of degree requirements for Bachelor of Computing (Computational Biology)
Modules MCs Subtotals
UNIVERSITY LEVEL REQUIREMENTS 20
PROGRAMME REQUIREMENTS 124
Common Essentials
CS1010   Programming Methodology10 4
CS1020   Data Structures and Algorithms I11 4
CS2010   Data Structures and Algorithms II11 4
CS2100   Computer Organisation 4
CS2102   Database Systems 4
CS2103T   Software Engineering12 4
ES2660   Communicating in the Information Age 4
Major Requirements
Level-1000 CS and LS major requirements  

 

 

 

 

 

CM1401 Chemistry for Life Sciences 4
CS1231 Discrete Structures 4
LSM1102   Molecular Genetics 4
LSM1106   Molecular Cell Biology 4
MA1101R   Linear Algebra I 4
MA1521 Calculus for Computing 4
Level-2000 CS and LS major requirements  

 

 

 

 

 

CS2220 Introduction to Computational Biology 4
CS2101 Effective Communication for Computing Professionals 4
Either
LSM2211 Metabolism and Regulation
or
LSM2232 Genes and Genomes
or
LSM2233 Cell Biology
4
LSM2241    Introductory Bioinformatics 4
ST2334 Probability and Statistics13 4
Level-3000 CS and LS major requirements
CS3230 Design & Analysis of Algorithms 4
CS3225 Combinatorial Methods in Bioinformatics or
MA3259 Mathematical Methods in Genomics
4
LSM3241 Bioinformatics and Biocomputing 4
Level-3000 Electives14; Choose any three from the following:
CS3225 Combinatorial Methods in Bioinformatics or MA3259 Mathematical Methods in Genomics
CS3240 Interaction Design
CS3241 Computer Graphics
CS3243 Introduction to Artificial Intelligence
CS3244 Machine Learning
12
Level-4000 CS and LS major requirements
CS4220 Knowledge Discovery Methods in Bioinformatics 4
LSM4241 Functional Genomics 4
Industrial Experience Requirement15 12
8 MCs of modules from Computational Biology Electives course list below:
CS4221 Database Application Design and Tuning
CS4231 Parallel and Distributed Algorithms
CS4234 Optimisation Algorithms
CS4235 Computational Geometry
CS4237 Systems Modelling and Simulation
CS4243 Computer Vision and Pattern Recognition
CS4244 Knowledge-Based Systems
CS4248 Natural Language Processing
CS5228 Knowledge Discovery and Data Mining
CS5234 Combinatorial & Graph Algorithms
CS5238 Advanced Combinatorial Methods in Bioinformatics
CS5340 Uncertainty Modelling in Artificial Intelligence
8
UNRESTRICTED ELECTIVES 16
Grand Total 160
1  Students should consult the CS Deputy Head (CS Programmes) in advance if they are interested in this option as industry courses may not be offered every year.
2   For students who opt for iLead or NOC, the additional MCs beyond the 12-MCs allocated to Industry Experience Requirement should be taken from Unrestricted Electives and/or exempted  modules.
3     CS1010 (4 MCs) can be replaced by CS1101S Programming Methodology (5 MCs).
4     CS1020 and CS2010 can be replaced by CS2020 Data Structures and Algorithms Accelerated. The remaining 2 MCs will be added to the Unrestricted Electives Requirements.
5      Students taking CS2103T Software Engineering must take CS2101 Effective Communication for Computing Professionals in the same  semester.
6      Students should choose ST2131 (Probability) and ST2132 (Mathematical Statistics) in place of ST2334 (Probability and Statistics) if they plan to pursue higher level statistics modules.
7      With the special permission from the UROP coordinator and Computational Biology Programme Coordinator, CP3208/CP3209 Undergraduate Research in Computing I/II can be used to replace two of the Level-3000 Computational Biology electives if the project is on Computational Biology.
8       Students in the Department of Computer Science who aim for Honours (Highest Distinction) must pass the CP4101 BComp Dissertation. Students with CAP of 4.0 or higher at the end of their fifth semester of undergraduate study may opt to replace the Industry Experience Requirement by CP4101 BComp Dissertation (12 MCs).
9      The Computational Biology (CB) Elective Course List may be revised from time to time to include new Computational Biology electives that are introduced and approved by the Department of Computer Science.
10     CS1010 (4 MCs) can be replaced by CS1101S Programming Methodology (5 MCs).
11     CS1020 and CS2010 can be replaced by CS2020 Data Structures and Algorithms Accelerated. The remaining 2 MCs will be added to the Unrestricted Electives Requirements.
12     Students taking CS2103T Software Engineering must take CS2101 Effective Communication for Computing Professionals in the same semester.
13     Students pursuing a double degree in Computer Science and Mathematics/Applied Mathematics will take ST2131 Probability and ST2132 Mathematical Statistics in place of ST2334 Probability and Statistics
14     With the special permission from the UROP coordinator and Computational Biology Programme Coordinator, CP3208/CP3209 Undergraduate Research in Computing I/II can be used to replace two of the Level-  3000 Computational Biology electives if the project is on Computational Biology.
15     Students in the Department of Computer Science who aim for high distinction must pass the CP4101 BComp Dissertation. Students with CAP of 4.0 or higher at the end of their fifth semester of undergraduate  study may opt to replace the Industry Experience Requirement by B.Comp Dissertation (12 MCs).

Concurrent Programme with Brown University on Computational Biology

This is a fast-track programme that allows deserving students to obtain the Bachelor of Computing (Computational Biology) from NUS and a Scientiae Magister in Computational Biology in Computer Science from Brown University within five years.

Please refer to Section R7 of Part II of this bulletin for details.

  Home / NUS Bulletin AY2017/18 / School of Computing / Undergraduate Education / Degree Requirements / Bachelor of Computing in Computational Biology