• Computational Biosciences

    Computational Biosciences


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Computational Biosciences

Computational studies of biological and biochemical systems at McMaster span a wide spectrum of approaches from molecular biology to population dynamics, and use a wide range of methods including statistical modeling, evolutionary algorithms, differential equations and nonlinear optimization. Many practical applications arise within this area, including drug design and gene sequencing for disease identification.

At the molecular level, the McMaster Institute for Molecular Biology and Biotechnology (MOBIX) is a world-class centre with a particular strength, among others, in Evolutionary and Genomics Biotechnology. Several researchers at McMaster are using computational models to investigate the following:

The field of Computational Biosciences will enhance the fragmented interactions between the individual researchers and will provide substantial opportunities for graduate students to profit from varied expertise and make lasting contributions to this area.


Clustering of amino acids according to their physical properties
(Paul Higgs)

Computational Biology

Computational model of the growth of a mollusc shell
(Jonathon Stone)

Molecular Modelling

Simulating Access of an Immunosuppressant Drug in the Potassium Channel Kv1.3
(Boris Zhorov)

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McMaster University - School of Computational Science and Engineering