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Australian State/Territory : QLD
Research Topic : Microarray
Scheme : ARC Future Fellowships
Status : Closed
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  • Funded Activity

    ARC Future Fellowships - Grant ID: FT110100254

    Funder
    Australian Research Council
    Funding Amount
    $816,756.00
    Summary
    RNA-based analysis for prediction of islet death in diabetes. Death of insulin-producing cells is a common feature in diabetes. Presently, a blood glucose test remains the only blunt instrument to diagnose diabetes. The RNA-based analysis for prediction of islet death in diabetes (RAPID) study links with eight clinical trials to test this newly developed non-invasive assay for predicting diabetes. Early diagnosis will help to reduce diabetic complications in later life.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT100100377

    Funder
    Australian Research Council
    Funding Amount
    $700,927.00
    Summary
    Genomics of temperature response in plants. Climate change is predicted to have negative impacts on Australian agriculture. This project will use genomic tools to uncover biological mechanisms for plant response to temperature that will help design crop varieties that are more tolerant to higher temperatures.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT180100186

    Funder
    Australian Research Council
    Funding Amount
    $918,125.00
    Summary
    Deciphering the genetic architecture of human complex traits. This project aims to develop statistical methods to integrate data from genetic studies of complex traits such as stature and cognition. Molecular phenotypes such as gene expression in large samples will be used to predict target genes and regulatory elements of those traits. Understanding the genetic basis of human complex traits is critical to longstanding questions in human and evolutionary biology. The project will also detect sig .... Deciphering the genetic architecture of human complex traits. This project aims to develop statistical methods to integrate data from genetic studies of complex traits such as stature and cognition. Molecular phenotypes such as gene expression in large samples will be used to predict target genes and regulatory elements of those traits. Understanding the genetic basis of human complex traits is critical to longstanding questions in human and evolutionary biology. The project will also detect signatures of natural selection in shaping the genetic variation in complex traits. The project will provide better understanding of complex traits in global populations and the history of human evolution, and will develop methods applicable in plant and animal contexts.
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