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Research Topic : INFECTIOUS DISEASE
Australian State/Territory : WA
Field of Research : Complex Physical Systems
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Complex Physical Systems (2)
Dynamical Systems in Applications (2)
Applied Mathematics (1)
Numerical and Computational Mathematics not elsewhere classified (1)
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Expanding Knowledge in the Mathematical Sciences (2)
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  • Funded Activity

    ARC Future Fellowships - Grant ID: FT110100896

    Funder
    Australian Research Council
    Funding Amount
    $816,268.00
    Summary
    Complex dynamical systems: inferring form and function of interacting biological systems. Often in biology a large number of simple parts interacting according to simple rules can result in behaviour that is rich and varied. This project aims to develop the mathematics of complex systems theory to describe how such collections of simple interacting parts can form large complicated structures, and to deduce what dynamical behaviour can result.
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    Funded Activity

    Discovery Projects - Grant ID: DP140100203

    Funder
    Australian Research Council
    Funding Amount
    $270,000.00
    Summary
    Quantifying complexity and measuring structure within complex systems. Most interesting systems are complex. The complex systems of interest in this project are characterised by a simple dynamical behaviour on each individual part; and a complicated web of interaction between the many distinct parts. The project will focus on the massive system of interacting neurones in the brain, and transmission of influenza via interpersonal contacts. This project will provide a better model of that web of i .... Quantifying complexity and measuring structure within complex systems. Most interesting systems are complex. The complex systems of interest in this project are characterised by a simple dynamical behaviour on each individual part; and a complicated web of interaction between the many distinct parts. The project will focus on the massive system of interacting neurones in the brain, and transmission of influenza via interpersonal contacts. This project will provide a better model of that web of interactions; and new methods for statistically validating this model against data. Existing models of complex networks are statistically biased so, by employing robust statistical methodologies, this problem will be rectified and provide a method for randomly choosing representative complex systems.
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