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Field of Research : Genetics
Field of Research : Bioinformatics Software
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Bioinformatics Software (5)
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP180100593

    Funder
    Australian Research Council
    Funding Amount
    $496,349.00
    Summary
    Real-time phylogenetics for food-borne outbreak surveillance. The project aims to introduce, for the first time, real-time evolutionary analysis of agricultural pathogens so that outbreaks affecting crops and the food supply can be managed precisely and rapidly. An expert team will implement a large-scale data analytics framework in user-friendly software that integrates Australian infectious disease genomics data with global data. Underpinning this work are new theory and algorithms that apply .... Real-time phylogenetics for food-borne outbreak surveillance. The project aims to introduce, for the first time, real-time evolutionary analysis of agricultural pathogens so that outbreaks affecting crops and the food supply can be managed precisely and rapidly. An expert team will implement a large-scale data analytics framework in user-friendly software that integrates Australian infectious disease genomics data with global data. Underpinning this work are new theory and algorithms that apply Sequential Monte Carlo to update phylogenetic analyses continuously as new data arrives. Expected outcomes include new knowledge of statistical algorithms for evolutionary analysis, relevant to biological disciplines beyond infectious disease; and enhanced capacity for infectious disease analysis.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT140100594

    Funder
    Australian Research Council
    Funding Amount
    $751,454.00
    Summary
    Uncovering microRNA decay regulation in mammalian cells. MicroRNAs (miRNAs) constitute a novel mechanism used by cells to regulate gene expression, however, very little is known about the mechanisms affecting miRNA accumulation. Characterisation of the kinetics of miRNA turnover is of paramount importance to establish the reliability of miRNAs as novel biomarkers. This project aims to characterise miRNA stability in mammalian cells, investigate mechanisms of turnover and establish their importan .... Uncovering microRNA decay regulation in mammalian cells. MicroRNAs (miRNAs) constitute a novel mechanism used by cells to regulate gene expression, however, very little is known about the mechanisms affecting miRNA accumulation. Characterisation of the kinetics of miRNA turnover is of paramount importance to establish the reliability of miRNAs as novel biomarkers. This project aims to characterise miRNA stability in mammalian cells, investigate mechanisms of turnover and establish their importance on the regulatory function of miRNAs. Such information is critical in the future development of targeted therapeutics.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT140100843

    Funder
    Australian Research Council
    Funding Amount
    $768,699.00
    Summary
    Understanding somatic mutation in plants: new methods, new software, new data. Somatic mutations accumulate as plants grow, affecting everything from short-term ecological interactions to long-term evolutionary dynamics. These mutations have important consequences for plant industry and conservation, but because they are so hard to measure almost nothing is known about them. This project aims to develop new methods and software to detect, analyse, and compare the genome-wide history of somatic m .... Understanding somatic mutation in plants: new methods, new software, new data. Somatic mutations accumulate as plants grow, affecting everything from short-term ecological interactions to long-term evolutionary dynamics. These mutations have important consequences for plant industry and conservation, but because they are so hard to measure almost nothing is known about them. This project aims to develop new methods and software to detect, analyse, and compare the genome-wide history of somatic mutation in individual plants, providing an unprecedented level of detail into an important but understudied source of biological variation. By applying these methods to an iconic experimental population, This project aims to provide the first insights into the genome-wide causes and consequences of somatic mutation in plants.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE120101127

    Funder
    Australian Research Council
    Funding Amount
    $375,000.00
    Summary
    An integrated statistical genetics framework for breeding superior wheat varieties. Genetic studies in agriculture are rapidly increasing in size and complexity in pursuit of genes behind desirable traits such as yield and water use efficiency. This project will address the need for efficient statistical methods to analyse genetic data and thus enable production of wheat varieties that will contribute to Australian food security.
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    Funded Activity

    Discovery Projects - Grant ID: DP160103474

    Funder
    Australian Research Council
    Funding Amount
    $491,900.00
    Summary
    Evolutionary analyses of short-read sequences from pooled samples. This project aims to provide biologists with a means of making sound, statistical inferences about evolution by using next-generation data from mixed samples. When biologists make statements about history, they use evolutionary trees, frequently reconstructed from the genetic data of many individuals. Next-generation sequencing provides large amounts of genetic data at low cost, but biologists have difficulty using these data for .... Evolutionary analyses of short-read sequences from pooled samples. This project aims to provide biologists with a means of making sound, statistical inferences about evolution by using next-generation data from mixed samples. When biologists make statements about history, they use evolutionary trees, frequently reconstructed from the genetic data of many individuals. Next-generation sequencing provides large amounts of genetic data at low cost, but biologists have difficulty using these data for evolutionary research, particularly when they sample mixtures of DNA from many individuals. The anticipated value of this project is that it allows evolutionary biologists to capitalise on the benefits of next-generation sequencing, without sacrificing their ability to make reliable inferences about history.
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