Mathematical Biology (MAST90011)

Graduate courseworkPoints: 12.5Not available in 2023

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Overview

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Modern techniques have revolutionised biology and medicine, but interpretative and predictive tools are needed. Mathematical modelling is such a tool, providing explanations for counter-intuitive results and predictions leading to new experimental directions. The broad flavour of the area and the modelling process will be discussed. Applications will be drawn from many areas including population growth, epidemic modelling, biological invasion, pattern formation, tumour modelling, developmental biology and tissue engineering. A large range of mathematical techniques will be discussed, for example discrete time models, ordinary differential equations, partial differential equations, stochastic models and cellular automata.

Intended learning outcomes

After completing this subject, students will:



  • appreciate the context in which continuum and discrete modelling may arise in mathematical modelling;
  • have high level mathematical tools and knowledge that can be used to model a range of problems in mathematical biology;
  • have the ability to implement physically justified approximations to solve complex problems;
  • have been exposed to both computational and analytical tools, and understand the various contexts in which they can be applied;
  • have the ability to pursue further studies in this and related areas.

Generic skills

In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop generic skills that will assist them in any future career path. These include:

  • problem-solving skills: the ability to engage with unfamiliar problems and identify relevant solution strategies;
  • analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis;
  • collaborative skills: the ability to work in a team;
  • time-management skills: the ability to meet regular deadlines while balancing competing commitments.

Last updated: 10 November 2023

Eligibility and requirements

Prerequisites

Code Name Teaching period Credit Points
MAST20030 Differential Equations
Semester 2 (On Campus - Parkville)
 12.5

OR

Equivalent

OR

All of

Code Name Teaching period Credit Points
MAST30030 Applied Mathematical Modelling
Semester 1 (On Campus - Parkville)
 12.5

MAST30029 Partial Differential Equations (pre-2014)

Corequisites

None

Non-allowed subjects

None

Inherent requirements (core participation requirements)

The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.

Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home

Last updated: 10 November 2023

Assessment

DescriptionTimingPercentage

Up to 50 pages of written assignments (three assignments worth 20% each, due early, mid and late in semester)

  • 50 pages
Throughout the teaching period60%

A written examination

  • 2 hours
During the examination period40%

Last updated: 10 November 2023

Dates & times

Not available in 2023

Time commitment details

170 hours

Last updated: 10 November 2023

Further information

  • Texts

    Prescribed texts

    TBA

    Recommended texts and other resources

    Edelstein-Keshet, L. Mathematical Models in Biology. McGraw Hill, 1987.
    Murray, J. D. Mathematical Biology. Springer Verlag, 1990 (or the new 2 Volume Third edition, 2003).
    Britton, N. F. Essential Mathematical Biology, Springer, 2003.
    Dr Vries, G., Hillen T., Lewis, M., Muller, J. and Schonfisch, B. A Course in Mathematical Biology. SIAM, 2006.

  • Related Handbook entries

    This subject contributes to the following:

    TypeName
    CourseDoctor of Philosophy - Engineering
    CoursePh.D.- Engineering
    CourseMaster of Science (Mathematics and Statistics)
    CourseMaster of Philosophy - Engineering
    Informal specialisationMathematics and Statistics
  • Available through the Community Access Program

    About the Community Access Program (CAP)

    This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.

    Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants

    Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.

  • Available to Study Abroad and/or Study Exchange Students

    This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.

Last updated: 10 November 2023