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Field of Research : Biostatistics
Australian State/Territory : VIC
Status : Closed
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  • Funded Activity

    Discovery Projects - Grant ID: DP170103076

    Funder
    Australian Research Council
    Funding Amount
    $335,000.00
    Summary
    Mathematical and statistical methods for modelling invivo pathogen dynamics. This project aims to develop mathematical models and Bayesian statistical methods that better capture how natural defence responses and drugs help control infection. When viruses (e.g. influenza) or parasites (e.g. malaria) invade the human body, they begin to replicate. To date, only simple mathematical models have been developed to capture these processes, and these models are not well formulated. This project will im .... Mathematical and statistical methods for modelling invivo pathogen dynamics. This project aims to develop mathematical models and Bayesian statistical methods that better capture how natural defence responses and drugs help control infection. When viruses (e.g. influenza) or parasites (e.g. malaria) invade the human body, they begin to replicate. To date, only simple mathematical models have been developed to capture these processes, and these models are not well formulated. This project will improve biomathematics and biostatistical algorithms for pathogen dynamics and is ultimately expected to benefit public health and clinical research aimed at alleviating the effect of infectious diseases on human health.
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    Funded Activity

    Enhancing Aspects Of Time-to-event Analysis Methodology In Randomised Trials

    Funder
    National Health and Medical Research Council
    Funding Amount
    $548,446.00
    Summary
    Time-to-event analysis is a statistical method for examining the occurrence of disease-related events in individuals followed for varying periods of time. The method is widely used in health research. The technicalities of the methods are subtle and by paying careful attention to these this grant will provide extended methods, new software, and apply methods more effectively to gain new insights to disease progress, and to enhance the efficiency of health research.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE170100785

    Funder
    Australian Research Council
    Funding Amount
    $345,491.00
    Summary
    Mathematical and statistical modelling of antimalarial drug action. This project aims to develop a mathematical model to optimise global antimalarial treatment policy. Malaria-causing parasites are resistant to the most potent antimalarial drug available. If left unaddressed, a catastrophic rise in global malaria incidence and mortality could occur. Changes to global antimalarial treatment policy increasingly rely on mathematical models, but they do not encompass recent breakthroughs in antimala .... Mathematical and statistical modelling of antimalarial drug action. This project aims to develop a mathematical model to optimise global antimalarial treatment policy. Malaria-causing parasites are resistant to the most potent antimalarial drug available. If left unaddressed, a catastrophic rise in global malaria incidence and mortality could occur. Changes to global antimalarial treatment policy increasingly rely on mathematical models, but they do not encompass recent breakthroughs in antimalarial drug action and the immune response. This project’s model is expected to improve antimalarial drug dosing regimens and control the spread of antimalarial drug resistance.
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    Funded Activity

    Discovery Projects - Grant ID: DP150102472

    Funder
    Australian Research Council
    Funding Amount
    $295,900.00
    Summary
    New statistical approaches for analysing foodwebs and species distributions. Identifying how species are distributed over the landscape, interact and self-organise into foodwebs are central goals in Ecology. This project aims to provide innovative new Bayesian modelling tools to improve our understanding of species distributions and their foodweb networks. It is expected to develop a general framework for extending species distribution models to deal with multiple species, incorporating both the .... New statistical approaches for analysing foodwebs and species distributions. Identifying how species are distributed over the landscape, interact and self-organise into foodwebs are central goals in Ecology. This project aims to provide innovative new Bayesian modelling tools to improve our understanding of species distributions and their foodweb networks. It is expected to develop a general framework for extending species distribution models to deal with multiple species, incorporating both their interactions as well as errors in detection. The project also hopes to develop a robust Bayesian methodology for partitioning complex foodweb networks into ecologically relevant compartments as there are currently no reliable methods to achieve this. Both projects are of relevance to conservation policy and management of threatened species.
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    Funded Activity

    Discovery Projects - Grant ID: DP190103188

    Funder
    Australian Research Council
    Funding Amount
    $410,000.00
    Summary
    Improved models to understand the genomic architecture of complex traits. This project aims to improve modelling of the genetics underlying complex traits. The project will develop and test models for using genome-wide genetic data to investigate how much heritability (genetic effect) underlies traits of interest, where it lies in the genome, and how much of it is shared across traits. The new models will be implemented in statistical algorithms in a freely-available software package. This proj .... Improved models to understand the genomic architecture of complex traits. This project aims to improve modelling of the genetics underlying complex traits. The project will develop and test models for using genome-wide genetic data to investigate how much heritability (genetic effect) underlies traits of interest, where it lies in the genome, and how much of it is shared across traits. The new models will be implemented in statistical algorithms in a freely-available software package. This project expects to increase understanding of biological mechanisms, the efficiency of genetic association analyses and the accuracy of genomic prediction, including the effects of interventions. The project will adapt human models to a wider range of organisms, in particular bacteria.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE190100046

    Funder
    Australian Research Council
    Funding Amount
    $387,000.00
    Summary
    Fortifying our digital economy: advanced automated vulnerability discovery. This project aims to enable security researchers to detect critical vulnerabilities in large software systems with maximal efficiency, cost-effectively, and with known statistical accuracy. The aim is to develop advanced high-performance fuzzers that effectively thwart malware attacks, ransomware epidemics, and cyber terrorism by exposing security flaws before they can commence. The project will employ a well-established .... Fortifying our digital economy: advanced automated vulnerability discovery. This project aims to enable security researchers to detect critical vulnerabilities in large software systems with maximal efficiency, cost-effectively, and with known statistical accuracy. The aim is to develop advanced high-performance fuzzers that effectively thwart malware attacks, ransomware epidemics, and cyber terrorism by exposing security flaws before they can commence. The project will employ a well-established statistical framework utilised in ecology research to provide fundamental insights to boosting the efficiency of software vulnerability discovery, and on the trade-off between investing more resources and gaining better cyber security guarantees. As our reliance on new technologies is ever growing, this project equips Australia to curb cyber crime cost-effectively.
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    Funded Activity

    Statistical Bioinformatics For Genomic Research

    Funder
    National Health and Medical Research Council
    Funding Amount
    $763,409.00
    Summary
    New genomic technologies are revolutionizing biological research. RNA-seq is a recently developed high-throughput sequencing technology that provides scientists with much more detail how genes are regulated and expressed than any earlier technology. New tools developed by Professor Gordon Smyth are allowing researchers to use RNA-Seq technology to more accurately determine which genes are genuinely changing in the development of cancers and in response to cancer treatments.
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    Showing 1-7 of 7 Funded Activites

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