APP MTH 7049 - Applied Mathematics Topic D

North Terrace Campus - Semester 2 - 2019

Please contact the School of Mathematical Sciences for further details, or view course information on the School of Mathematical Sciences web site at

  • General Course Information
    Course Details
    Course Code APP MTH 7049
    Course Applied Mathematics Topic D
    Coordinating Unit Mathematical Sciences
    Term Semester 2
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Available for Study Abroad and Exchange Y
    Assessment Ongoing assessment, exam
    Course Staff

    Course Coordinator: Dr Edward Green

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    In 2019, the topic of this course is Mathematical Biology and Physiology.


    For centuries, mathematical models have been used in the physical sciences to help us understand problems such as the propagation of light, the motion of the planets, or the flow of fluids. More recently, mathematical models have been applied to problems in the life sciences, yielding important new insights into biological problems, and stimulating the development of new mathematics. This cross-fertilisation between the disciplines makes mathematical biology and physiology one of the most exciting (and challenging) areas of applied mathematics. In this course, we will study some important biological problems where mathematical models in the form of systems of ODEs and PDEs have produced new understanding. Unfortunately, most biologically interesting models cannot be solved analytically, and so we we need to develop expertise in alternative techniques for understanding their behaviour, including phase plane analysis, bifurcation theory and perturbation methods.

    Topics covered will include:
    -enzyme-catalysed reactions
    -ion transport and propagation of signals in nerve cells (Hodgkin-Huxley equations)
    -model development using conservation laws
    -models for cell movement
    -travelling waves
    -development of patterns in tissues (Keller-Segel model, Turing patterns)
    -tissue growth

    Assumed knowledge for the course is a basic understanding of ODEs and PDEs, as covered in Modelling with ODEs III and Waves and PDES III.

    Learning Outcomes

    On successful completion of this course, students will be able to:

    1. develop ODE models for enzyme-catalysed reactions using the Law of Mass Action;

    2. understand how Michaelis-Menten kinetics can be derived using perturbation theory;

    3. understand and explain models for ion transport;

    4. use phase-plane techniques to study the dynamics of ODE models such as the Hodgkin-Huxley equations;

    5. understand conservation laws, and be able to use them to develop new models;

    6. understand what is meant by a travelling wave solution, and be able to demonstrate their existence for Fisher's equation and other; systems;

    7. understand the principles underpinning the Keller-Segel and Turing models for pattern formation, and use stability analysis to predict when it will occur in these and similar models;

    8. recognise free boundary problems arising in tumour growth, and use some basic analytical techniques to study them.
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    Self-awareness and emotional intelligence
    • a capacity for self-reflection and a willingness to engage in self-appraisal
    • open to objective and constructive feedback from supervisors and peers
    • able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
  • Learning Resources
    Required Resources
    Recommended Resources
    L. Edelstein-Keshet, Mathematical Models in Biology, SIAM Classics in Applied Mathematics, 2005.

    J. D. Murray, Mathematical Biology (two volumes), Springer, 2002.
    Online Learning
    The course will have an active MyUni website.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    The lecturer guides the students through the course material in 30 lectures. Students are expected to engage with the material in the lectures. Interaction with the lecturer and discussion of any difficulties that arise during the lecture is encouraged. Fortnightly homework assignments help students strengthen their understanding of the theory and their skills in applying it, and allow them to gauge their progress.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Activity Quantity Workload hours
    Lectures 30 90
    Assignments 4 66
    Total 156


    Learning Activities Summary
    Lecture outline

    Enzyme catalysed reactions, the Law of Mass Action, Michaelis-Menten kinetics (4 Lectures).

    Ion transport, excitable systems the Hodgkin-Huxley equations (5 Lectures).

    Conservation laws, cell movement, reaction-advection diffusion equations, age-structured models (6 Lectures).

    Fisher's equation, travelling waves (4 Lectures)

    Pattern formation, Keller-Segel model, linear stability analysis, Turing patterns, diffusion-driven instability (6 lectures)

    Domain growth, free boundary problems, avascular tumour models, development of the necrotic core (4 Lectures).

    Summary (1 Lecture).
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment task Task type Weighting Learning outcomes
    Assignments Formative and summative 30% All
    Exam Summative 70% All
    Assessment Related Requirements
    An aggregate score of 50% is required to pass the course.
    Assessment Detail
    There will be four assignments worth 30% of the total mark. The remaining 70% will come from the exam
    Assignments must be handed in person to the lecturer or submitted in the assigned assignment box if they are to be marked.

    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy ( course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
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