Sidebar    Computational Biology

The field of computational biology has become one of the most important disciplines of both computer science and of the life sciences. This relatively young field emerged from long-standing cross-pollination: some problems in biology required algorithmic solutions, and some concepts in biology inspired computational innovation. The field has grown along with the explosive growth of data generated in the post-genomic era. DNA sequencing data, imaging data, simulation data, and experimental data of all sorts have made computational biology indispensable. But the real revolution of these technical and computational advances is that new experiments are now thinkable, new questions are now askable. Since the determination of the three-dimensional structure of DNA over half a century ago, molecular and structural biology have experienced extraordinary progress. This deeper understanding is obtained through the interdisciplinary interaction of Biology with the Computational and Mathematical Sciences, which has led to the emergence and recognition of Computational Biology as a discipline at the interface of these sciences. This discipline has today a well-connected peer community, with a host of established conferences and publication venues, and a vigorous professional market, spearheaded by the pharmaceutical and biomedical industries.

Programme Structure and Curriculum Rationale

Launched in 2004, this four-year programme provides a multidisciplinary education that produces graduates equally at ease with algorithm design, statistical analysis, and programming as they are with biochemistry, cell biology, and genomics. Graduates of the computational biology programme may enter the workforce and contribute to cutting-edge industries, or may go on to postgraduate research.

Science students accepted into the programme enter a four-year track that leads to a B.Sc. (Hons.) in Computational Biology. The programme is structured so that students read a basket of core multidisciplinary modules in their first two years of study and proceed to an upper division specialised track in the next two years.

The lower division modules embrace a fundamental disciplinary understanding essential for a computational biologist. These fundamentals include:

  • Mathematical foundations, including calculus, linear algebra, discrete mathematics and principles of mathematical reasoning and proof.
  • Statistical foundations, including probability, univariate and multivariate statistics, and tools in mathematical statistics.
  • Computational foundations, including computer programming in two or more modern programming languages, algorithm design, and computational complexity.
  • Life Sciences fundamentals, including molecular biology, biochemistry, cell biology, and genomics
  • Computational biology and bioinformatics foundations

The upper division specialised track will strengthen the student’s knowledge in the theoretical foundations of DNA/protein sequence analysis, computational analysis of genomic data, and more. Depending on their interest, students may specialise in more advanced statistical issues, biological applications, or computer science topics.

Career Prospects

Graduates from the programme will be equipped for a career as a researcher, analyst or engineer in the fast-paced pharmaceutical, biomedical or biotechnology industries. This will also help meet the demand of the local market for talents with such skill sets. Moreover, the breadth of instruction will pave the way for students with a passion for computational biology to pursue graduate studies in bioinformatics, computer science, or many areas of life sciences.

Graduation Requirements

Programme Requirements MCs
University Requirements
5 x General Education Modules 20 20
Faculty Requirements
CM1401 Chemistry for Life Sciences [1]
LSM1102 Molecular Genetics [1]
MA1101R Linear Algebra I
SP1541 Exploring Science Communication through Popular Science [2]


Major Requirements
Programme Requirements MCs
Level-1000 / 2000 Essential [1]


CS1010S or CS1010X Programming Methodology [3] 4
CS2040 Data Structures and Algorithms 4
CS1231 Discrete Structures or MA1100 Fundamental Concepts of Mathematics 4
LSM1106 Molecular Cell Biology 4
MA1102R   Calculus 4
CS2220     Introduction to Computational Biology [4] OR LSM2241 Introductory Bioinformatics 4
LSM2211 Metabolism and Regulation OR
LSM2232 Genes and Genomes OR
LSM2233 Cell Biology
ST2131 Probability and ST2132 Mathematical Statistics 8
Level-3000 Essential
MA3259  Mathematical Methods In Genomics 4 8
LSM3241  Genomic Data Analysis 4
Programme Requirements MCs
Level-3000 Electives [4] (Choose Four Modules) –
[Any two modules from option A and any two modules from option B]

Option A

CS2102        Database System
CS3103        Computer Networks Practice
CS3230        Design and Analysis of Algorithms
CS3223        Database Systems Implementation
CS3240        Interaction Design
CS3241        Computer Graphics
CS3243        Introduction to Artificial Intelligence
CS3244        Machine Learning

Option B

LSM3211      Fundamental Pharmacology
LSM3223      Immunology
LSM3225      Molecular Microbiology
LSM3231      Protein Structure and Function
LSM3232      Microbiology
LSM3233      Developmental Biology
LSM3243      Molecular Biophysics
PC3267        Biophysics II [5]
MA3233       Combinatorics and Graphs II
ST3131        Regression Analysis
ST3240        Multivariate Statistical Analysis
ST3232        Design and analysis of experiments
ST3233        Applied time series analysis
ST3236 /      Stochastic Process 1
ST3247        Simulation
ST3248        Statistical Learning I


Level-4000 Essential


ZB4199         Honours Project in Computational Biology OR
ZB4299         Applied Project in Computational Biology
ZB4171         Advanced Topics in Bioinformatics 4
Programme Requirements MCs
Level-4000 Electives (Choose Three Modules) –
[Any two modules from either option A or option B or option C, and
the remaining third module to be selected from the Option not chosen]


Option A

CS4220         Knowledge Discovery Methods in Bioinformatics
CS4221         Database Applications Design and Tuning
CS4231         Parallel and Distributed Algorithms
CS4224         Distributed Databases
CS4225         Big Data Systems for Data Science
CS4234         Optimisation Algorithms
CS4243         Computer Vision and Pattern Recognition
CS4244         Knowledge-Based Systems
CS4248         Natural Language Processing
CS4330         Combinatorial Methods in Bioinformatics

Option B

LSM4211       Toxicology
LSM4212       Pharmacogenetics and Drug Response
LSM4213       Systems Neurobiology
LSM4221       Drug discovery and Clinical Trials
LSM4222       Advanced Immunology
LSM4224       Free Radicals and Antioxidant Biology
LSM4226       Infection and Immunity
LSM4231       Structural Biology
LSM4232       Advanced Cell Biology
LSM4241       Functional Genomics
LSM4242       Protein Engineering

Option C
MA4251/       Stochastic Processes II
PC4267         Biophysics III
ST4231         Computer Intensive Statistical Methods
ST4234         Bayesian Statistics
ST4242         Analysis of Longitudinal Data
ST4248         Statistical Learning II
Unrestricted Elective Modules [4]




Note 1:
Modules are part of the lower division requirements for the Computational Biology Programme.

Note 2:
The following groups of students who are precluded from reading SP1541/ES1541:

  • Students who are UTown residents and have read and passed the IEM, UTW and UWC modules
  • Students who are RVRC residents and have read and passed ES1601 module
  • Students who are in SPS and have read and passed the SP2171
  • Students who are in USP and have read and passed the UWC2101% modules

will have to read another module instead of SP1541 to fulfil 4 MCs of Faculty requirements, except for students in SPS who have read and passed SP2171 as SP2171 can be used to fulfil 4 MCs of Faculty Requirements.

Note 3:
CS1101S Programming Methodology (5 MCs prior to AY2018/19, 4 MCs wef AY2018/19) may be read as an alternative to CS1010S. This module is suitable for those with prior experience in Python. Do note that registration to this module is subject to host availability.

Note 4:
ZB3288 UROPS in Computational Biology can be taken in fulfilment of 4 MCs from any of the options in the level-3000 elective list.

Note 5:
Students may wish to read PC2267 Biophysics I as an unrestricted elective module to meet the prerequisites required for PC3267 Biophysics II (Level-3000 major elective module).

Summary of Requirements B.Sc. (Hons.)
University Requirements 20 MCs
Faculty Requirements 16 MCs
Major Requirements 88-92 MCs
Unrestricted Elective Modules 32-36 MCs
Total 160 MCs