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Australian State/Territory : WA
Research Topic : Bioinformatics
Australian State/Territory : VIC
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  • Funded Activity

    Developing Interpretable Machine Learning Models For Clinical Imaging And Single-cell Genomics

    Funder
    National Health and Medical Research Council
    Funding Amount
    $1,312,250.00
    Summary
    Machine learning methods will be vital to make best use of the deluge of data generated by high-throughput technologies in biomedical science. To get the most out of these models, however, we need to be able to unpack the 'black box'. I will use curated clinical and public research data to benchmark and develop interpretable deep learning models and software tools. These models will be used for breast cancer screening programs and for analysis of complex, large-scale single-cell genomics data.
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    Funded Activity

    Preparing Australia For Genomic Medicine: A Proposal By The Australian Genomics Health Alliance

    Funder
    National Health and Medical Research Council
    Funding Amount
    $25,000,000.00
    Summary
    The sequencing of the human genome brings the possibility of more accurate identification of the underlying basis of many diseases. This technology has moved so rapidly, however, that clinical access has been limited. In this application, a national alliance of clinicians, researchers, health economists and policymakers will evaluate the case for clinical genomics across inherited disease and cancer, determine how best to deliver this to the patient and train a capable workforce.
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    Funded Activity

    Identification Of Glaucoma Susceptibility Variants By Exome Sequencing In Extended Pedigrees Showing Prior Evidence Of Gene Segregation.

    Funder
    National Health and Medical Research Council
    Funding Amount
    $694,002.00
    Summary
    Primary open angle glaucoma is a chronic eye disease and one of the leading causes of visual impairment and blindness worldwide. This study will use cutting-edge genetic methods to look at the entire coding component of the human genome (exome) in 271 individuals from large glaucoma families. Our previous studies have shown that these families carry genetic variants that increase disease risk. In this investigation we aim to identify these genes, with the hope they may offer novel targets for tr .... Primary open angle glaucoma is a chronic eye disease and one of the leading causes of visual impairment and blindness worldwide. This study will use cutting-edge genetic methods to look at the entire coding component of the human genome (exome) in 271 individuals from large glaucoma families. Our previous studies have shown that these families carry genetic variants that increase disease risk. In this investigation we aim to identify these genes, with the hope they may offer novel targets for treatment or diagnosis.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP230101795

    Funder
    Australian Research Council
    Funding Amount
    $569,146.00
    Summary
    Next generation high throughput lipidomics using adaptive modelling. This project aims to develop a unique high-throughput method to capture the lipidomic profile of human plasma suitable for large human population screening. Lipids are fundamental to every biological system, but our understanding of their regulation in humans have been largely superficial. By incorporating a new lipidomics approach, with genomic data, this project aims to expand our understanding of human biology by identifying .... Next generation high throughput lipidomics using adaptive modelling. This project aims to develop a unique high-throughput method to capture the lipidomic profile of human plasma suitable for large human population screening. Lipids are fundamental to every biological system, but our understanding of their regulation in humans have been largely superficial. By incorporating a new lipidomics approach, with genomic data, this project aims to expand our understanding of human biology by identifying regulators of lipid metabolism. The large diversity in humans necessitate sufficient sample sizes to identify true genetic regulators, but to date techniques capturing phenotypic data (lipids) have been largely limited. It is anticipated that this study will identify new regulators of lipid metabolism in humans.
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