Biological systems are characterised by complex interactions that may be understood through the construction and application of mathematical models. Quantitative analysis is becoming an increasingly important component of biological research as a result of technological developments, which generate unprecedented amounts of biological data. Recent trends in the way biological research is done have generated rapid growth in the fields of bioinformatics, biostatistics and mathematical modelling of biological systems. Quantitative and computational approaches are now needed to address many of the important unsolved problems of modern biology.

This major will equip students with appropriate skills in mathematics to complement a solid foundation in biology. It is intended to be accompanied by further studies in mathematics, biology, statistics, or computer science. This major is also suitable for students who wish to continue to postgraduate research in one of these areas.

## Learning Outcomes

- Master the ideas and concepts of Calculus, Linear Algebra and Differential Equations and develop the ability to apply the acquired knowledge to analyse a specific problem and identify the mathematics that is required to find its solution.
- Gain a basic understanding of the ideas and concepts of Probability and Statistics.
- Apply conceptual knowledge of biological principles and processes including evolution and diversity of organisms, inheritance, storage and utilisation of information and the structure and function of molecules, cells and biological systems, to a range of disciplinary and inter-disciplinary contexts.
- Design biological experiments, and analyse and interpret experimental results using appropriate quantitative methods.
- Demonstrate capacity for mathematical reasoning through analysing, proving and explaining concepts from bioinformatics and biological modelling.
Describe and apply a variety of methods in bioinformatics and functional genomics, including scientific programming, interpret current literature in areas of bioinformatic practice and evaluate research methodology in the context of bioinformatic analysis of DNA sequence data.

## Other Information

To complete this major, students must also complete the following courses:

These courses can form part of a Foundational Science minor, another science minor/major or sequence of science electives. If a student is in a Flexible Double Degree, the courses can only contribute towards one degree.

**Advice for first year students:**

- You need to enrol in (MATH1013 or MATH1115), (MATH1014 or MATH1116), BIOL1003 and BIOL1004
- If you think you may want to do honours in Mathematics you are advised to take MATH1115 and MATH1116.

**Additional advice:**

- The courses COMP1040 (or COMP1730) are recommended for this Major.
- This Major can easily be taken in conjunction with either the Advanced Quantitative Biology Specialisation or with a Minor in Mathematics (only two additional MATH coded course needed after completing all the requirements of this Major). Other suggested Minors are in Biology, Applied Statistics, Computer Science or Chemistry.
- Students interested in doing a Major in Quantitative Biology but who do not have an appropriate Mathematics background to enrol in MATH1013 may do MATH1003 before beginning MATH1013.
- For students taking BIOL3208 or MATH3349 as part of this specialisation, the research project must be in the field of quantitative biology.

Students who need further information should contact the academic convener of the Quantitative Biology Major.

Back to the top## Requirements

This major requires the completion of 48 units, which must consist of:

18 units from the completion of the following compulsory courses:

BIOL1003 Biology 1: Evolution, Ecology and Genetics (6 units)

BIOL2151 Genetics (6 units)

MATH2307 Bioinformatics and Biological Modelling (6 units)

6 units from the completion of a 1000- level MATH course from the following list:

MATH1013 Mathematics and Applications 1 (6 units)

MATH1115 Advanced Mathematics and Applications 1 (6 units)

6 units from the completion of a Statistics course from the following list:

STAT1003 Statistical Techniques (6 units)

STAT1008 Quantitative Research Methods (6 units)

BIOL2202 Experimental Design and Analysis in Biology (6 units)

18 units from the following list:

BIOL3157 Bioinformatics & Its Applications (6 units)

MATH3353 Advanced Mathematical Bioinformatics (6 units)

MATH3511 Scientific Computing (6 units)

BIOL3207 Data Science for Biologists (6 units)

BIOL3208 Biology Research Project (6 units)

MATH3349 Special Topics in Mathematics (6 units)

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