Computer Science

Computational Science: COMPSCI 369 Semester 1, City Campus

The number of ways that computers are used in the sciences are many, varied and often extremely sophisticated. The focus of this course will be on "computational science" which involves constructing mathematical models that can be simulated, analysed and solved using computational methods.

The course is split into two parts: in the first 3-4 weeks, we'll look at techniques for finding the roots of equations, solving systems of linear equations and decomposing matrices. These techniques are basic to areas of research known as computational engineering, numerical analysis and applied linear algebra.

In the remaining 8-9 weeks, we'll turn to computational biology, with a focus on bioinformatics and phylogenetics. There, we see how a wide range of computational and mathematical techniques have revolutionised an area of science and allowed us to analyse and interpret huge amounts of genetic data. This area of study has helped us better understand, among other things, the basic workings of life, our evolutionary history, the causes of inherited diseases and the spread of infectious disease. From a computational point of view, computational biology is a fascinating and active area of research. The techniques we'll study in this part of the course include stochastic and probabilistic modelling, simulation, dynamic programming, estimation and inference.

The examinable material in this course is summarised in the learning outcomes.

Learning Activities

These are based on lectures, graded assignments, and your reading of the recommended books. All of these ingredients are necessary if you are to get the most out of the course. There are three assignments (worth 10% each) designed to complement the material from class, as well as the reading from recommended textbooks and Internet resources.

Required Text

There is no required textbook because no single textbook covers all of the material covered in the course. Reading materials drawn from several textbooks, as well as the primary literature will be useful.

Recommended Reading

  • Computational and numerical methods:
    • Anton, H. and Busby, R.C.: Contemporary Linear Algebra, (Wiley 2003)
    • Gilbert Strang : Computational Science and Engineering, (Wellesley - Cambridge Press 2007)
  • Computational biology:
    • Durbin R, Eddy S.R., Krogh A. and Mitchison G. : Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, (Cambridge University Press 1998).
    • Higgs P.G. and Attwood T.K. : Bioinformatics and Molecular Evolution, (Blackwell Publishing, 2005)
    • Jones N.C. and Pevzner P.A. : An Introduction to Bioinformatics Algorithms, (MIT Press, 2004).

Seeking Assistance

For assistance with course material and course work you should feel free to contact the tutor or lecturer either via email or in person. The Department of Computer Science also has a team of support staff (see the posters around the labs for support contacts) who are happy to provide guidance on more general issues to do with your study in computer science.

Catching up on missed lectures and labs

If you miss a lecture, you should catch up as soon as possible by reading the corresponding sections of the notes or viewing the lecture recordings posted on this website.

If you are unable to meet a deadline for an assignment, please contact the lecturer in advance of the due date.

If you miss the test/exam for any valid reason, or you sit the test/exam but believe that your performance was impaired for some reason, then you may be able to apply for an aegrotat, compassionate or special pass consideration. Information about aegrotats and compassionate consideration is given here.


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