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MODULE F: Computational Biophysics Dr Paul Abbott

Course Information

The course is a "hands-on" laboratory style course consisting of 6 x 2 hour lab sessions worth a total of 100%.


The purpose of computing is insight, not numbers Richard Hamming

What is Computational Biophysics?

The broad categories of computational biophysics are Simulation, Visualisation and Modelling. At a finer scale, it embraces a wide range of areas including numerical methods, algorithms and data analysis. Simulation and modelling are usually taught by stressing numerical techniques this course focuses on using symbolic or computer algebra.

Course Objectives:

  1. to use computers as an aid to understanding real physical systems;
  2. learn about methods for the analysis of these systems.


  1. Mathematica Basics provides some of the background necessary for the following sessions:
    • Course Overview
    • References
    • Book-keeping
    • Getting Help
    • Basic Calculations
  2. Stochastic Processes presents applications of random number generators (rngs) in computer simulation of stochastic processes:
    • Random number generation
    • One dimensional random walk
    • Fitting data in the presence of noise
    • Modelling fern growth
    • Two dimensional random walk
  3. Molecular Conformation introduces numerical methods for conformational modelling, and for solving minimisation problems:
    • Preliminaries
    • Coulomb potential
    • Lennard-Jones potential
    • Ethane rotational conformation
  4. Population Dynamics appies numerical methods for discrete (iterative) models and for solving ordinary differential equations (ODEs) to models from population dynamics:
    • Discrete logistic equation for a single species
    • Continuous logistic equation for a single species
    • Kermack-MacKendrick disease model
  5. Fourier Transform introduces Fourier methods which have application in convolution or deconvolution of data, correlation and autocorrelation, filtering, and power spectrum estimation:
    • Definition of DFT
    • One-dimensional DFT
    • Two-dimensional DFT
    • Applications
  6. Action Potential models voltage-dependent membrane currents in the squid giant axon using the Hodgkin-Huxley formalism:
    • RC Circuit
    • Passive Transmission Line
    • Hodgkin-Huxley Model


You can submit your solutions as follows:

  1. Name your assignment. For example, Joanna Bloggs should name each assignment JB.nb (the .nb which stands for Mathematica Notebook, is automatic and hidden under Windows but is visible on Macintosh systems).
  2. Go to the appropriate subfolder of the Solutions Folder. E.g., for the Mathematica Basics assignment go to the Basics Folder. Under the Netscape File menu you will find the Upload File... command. Use this to submit your solution. Note that this folder is a "drop folder", i.e., its contents are not visible (so that other students cannot copy your solution).

If you have any problems, please contact rourkt01@student.uwa.edu.au.

Information on 2nd Year Biophysics Courses

Information on the Biophysics Honours Course

UWA Biophysics Homepage


Contact Information

To contact us directly, send e-mail to Ralph James (ralph@physics.uwa.edu.au) or Tim St.Pierre (stpierre@physics.uwa.edu.au)