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Socio-Economic Objective : Higher education
Field of Research : Statistics
Research Topic : Flow Analysis
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  • Funded Activity

    Discovery Projects - Grant ID: DP0773445

    Funder
    Australian Research Council
    Funding Amount
    $277,295.00
    Summary
    Simulating viral evolution and genetic complexity. This project has direct relevance to understanding the growth of viral infections, and therefore has possible practical applications in disease research and control. Examples of these are emerging diseases in humans such as those caused by HIV-1, SARS coronavirus and Dengue virus, which cause considerable human suffering throughout the world. A major part of current research into these diseases involves attempts to model the evolutionary geneti .... Simulating viral evolution and genetic complexity. This project has direct relevance to understanding the growth of viral infections, and therefore has possible practical applications in disease research and control. Examples of these are emerging diseases in humans such as those caused by HIV-1, SARS coronavirus and Dengue virus, which cause considerable human suffering throughout the world. A major part of current research into these diseases involves attempts to model the evolutionary genetics and dynamics of virus populations in order to understand how to control epidemics, develop vaccines and design drugs. The research program is designed to provide new computational modelling tools for this purpose, which may have wider applications as well.
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    Funded Activity

    Discovery Projects - Grant ID: DP0559864

    Funder
    Australian Research Council
    Funding Amount
    $247,000.00
    Summary
    Theory and applications of Bayesian and likelihood analyses for finite mixture, random effect and multinomial models. The expected outcomes of the project are: to establish the scientific value of modern Bayesian methods for statistical inference in a wider range of applications than previously available, to contribute to the greater unification of the current theories of statistical inference which are to some extent in conflict, and to provide a set of Bayesian analytic tools implemented in .... Theory and applications of Bayesian and likelihood analyses for finite mixture, random effect and multinomial models. The expected outcomes of the project are: to establish the scientific value of modern Bayesian methods for statistical inference in a wider range of applications than previously available, to contribute to the greater unification of the current theories of statistical inference which are to some extent in conflict, and to provide a set of Bayesian analytic tools implemented in widely available, free and open-source statistical software.
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