Mathematical Biology

University of Queensland

Course Description

  • Course Name

    Mathematical Biology

  • Host University

    University of Queensland

  • Location

    Brisbane, Australia

  • Area of Study

    Biology, Mathematics

  • Language Level

    Taught In English

  • Prerequisites

    MATH1051 and MATH1052

  • Course Level Recommendations


    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • Host University Units

  • Recommended U.S. Semester Credits
  • Recommended U.S. Quarter Units
  • Overview

    Course Description
    Mathematical modelling of biological systems, with a particular focus on neuroscience.
    Course Introduction
    Mathematical biology is an approach to understanding biological processes that is growing very rapidly in importance. It deals with mathematical models of biological phenomena in such diverse areas as neuroscience, physiology, ecology, genetics and medicine. Unlike many phenomena in the physical sciences to which mathematics has been widely and successfully applied for a very long time, biological phenomena tend to be characterized by a high degree of variability and complexity. The challenge in modelling them typically lies in identifying a small enough set of variables or aspects for the mathematics to be tractable, without failing completely to capture the essence of what is taking place. Unlike in many mathematics courses where much time is spent on finding solutions to well-defined mathematical problems, in this course a significant amount of time will be spent on the art of constructing models of biological systems, and also on the interpretation of solutions of these new sorts of models.
    In 2015 this course will focus primarily on mathematical neuroscience, with topics including biophysical models of the electrical properties of neurons, statistical and information-theoretic analyses of neuronal activity patterns, and models for how the wiring between neurons changes to allow brains to learn from experience. While this will inevitably involve learning some neuroscience, the general lessons about how to turn complicated biological phenomena into tractable mathematical models will be widely applicable. The mathematics used will include ordinary and partial differential equations, probability and statistics, matrix theory and optimisation theory.
    Learning Objectives
    After successfully completing this course you should be able to:
    • Transfer a biological hypothesis into a mathematical representation
    • Understand how models can be used to gain understanding of complex systems and to make predictions
    • Understand the advantages and disadvantages of different types of models
    • Create simple models of biological processes
    • Interpret the solutions of models
    • Write simple programs using MATLAB to solve mathematical problems that arise in models
    • Create models of the electrical properties of nerve cells, neural plasticity, and neural information coding.
    Class Contact
    2 Lecture hours, 2 Tutorial hours
    Assessment Summary
    Assignment 1: 5.55%
    Assignment 2: 5.55%
    Assignment 3: 5.55%
    Assignment 4: 5.55%
    Assignment 5: 5.55%
    Aissignment 6/7: 11.1%
    Assignment 8: 5.55%
    Assignment 9: 5.55%
    Final Exam: 50%

Course Disclaimer

Courses and course hours of instruction are subject to change.

Eligibility for courses may be subject to a placement exam and/or pre-requisites.

Some courses may require additional fees.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.