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Current Selection
Status : Active
Field of Research : Bioinformatics
Research Topic : Cell Reprogramming
Australian State/Territory : NSW
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Bioinformatics (6)
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  • Researchers (24)
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  • Active Funded Activity

    ARC Future Fellowships - Grant ID: FT210100355

    Funder
    Australian Research Council
    Funding Amount
    $925,739.00
    Summary
    Dissecting cell cycle regulation using programmable gene editing technology. This program aims to harness the unprecedented power of CRISPR-Cas13 gene-editing technology to develop high-throughput tools to explore the role of RNA regulation in cell cycle control. This project expects to generate new knowledge about cell division and RNA biology by utilizing this new technology and applying interdisciplinary approaches. Expected outcomes of this proposal include new research tools capable of broa .... Dissecting cell cycle regulation using programmable gene editing technology. This program aims to harness the unprecedented power of CRISPR-Cas13 gene-editing technology to develop high-throughput tools to explore the role of RNA regulation in cell cycle control. This project expects to generate new knowledge about cell division and RNA biology by utilizing this new technology and applying interdisciplinary approaches. Expected outcomes of this proposal include new research tools capable of broadly addressing biological questions across multiple disciplines (e.g. from health to food production). This project intends to provide significant benefits, such as enhanced biological knowledge, multidisciplinary training opportunities and will build Australia’s capability in this rapidly expanding field.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220102196

    Funder
    Australian Research Council
    Funding Amount
    $530,000.00
    Summary
    Resurrecting Ancient Proteins to Unlock New Catalytic Activity. This project aims to study the proteins that nature uses to make penicillin and related antibiotics, and their prehistoric ancestors. By doing so, the project expects to deepen understanding of these important processes, open up ways to make new antibiotics, and generate new knowledge about protein evolution. Intended outcomes include new biocatalysts based on the ancient ones, new antibiotic compounds active against resistant bacte .... Resurrecting Ancient Proteins to Unlock New Catalytic Activity. This project aims to study the proteins that nature uses to make penicillin and related antibiotics, and their prehistoric ancestors. By doing so, the project expects to deepen understanding of these important processes, open up ways to make new antibiotics, and generate new knowledge about protein evolution. Intended outcomes include new biocatalysts based on the ancient ones, new antibiotic compounds active against resistant bacteria, and a richer understanding of how these proteins have evolved over the last 4 billion years. This promises significant benefits in the form of new ways to address the challenge posed by antimicrobial resistance to antibiotics, which is a serious threat to the continued effectiveness of current antibiotics.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200102903

    Funder
    Australian Research Council
    Funding Amount
    $650,000.00
    Summary
    Empirical and computational solutions for multi-omics single-cell assays. Emerging single-cell sequencing technologies are transforming molecular cell biology, but identifying novel cell types and their functions requires the integration of highly heterogeneous data. The development of computational methods able to extract biologically relevant results is hindered by the lack of high-quality datasets. This project aims to develop novel sequencing methodologies and generate data to drive our dime .... Empirical and computational solutions for multi-omics single-cell assays. Emerging single-cell sequencing technologies are transforming molecular cell biology, but identifying novel cell types and their functions requires the integration of highly heterogeneous data. The development of computational methods able to extract biologically relevant results is hindered by the lack of high-quality datasets. This project aims to develop novel sequencing methodologies and generate data to drive our dimension reduction multivariate method developments for data integration. By combining in silico and in vivo approaches, the project is anticipated to benefit scientists willing to work in cutting-edge single-cell research by providing useful protocols and tools to generate novel insights in cell biology.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210103811

    Funder
    Australian Research Council
    Funding Amount
    $912,619.00
    Summary
    Gene regulation by retroelement encoded natural antisense transcripts. Genetic information underpins all life on earth and is processed to make proteins, which determine the characteristics of an organism. However, only about 2% of our whole genome is made up of genes that encode proteins; the other 98% is non-coding and its function remains poorly understood. Aims and Significance: This proposal aims to utilise cutting edge genomic technologies to generate new knowledge about how the non-coding .... Gene regulation by retroelement encoded natural antisense transcripts. Genetic information underpins all life on earth and is processed to make proteins, which determine the characteristics of an organism. However, only about 2% of our whole genome is made up of genes that encode proteins; the other 98% is non-coding and its function remains poorly understood. Aims and Significance: This proposal aims to utilise cutting edge genomic technologies to generate new knowledge about how the non-coding genome regulates the expression of protein coding genes. Expected Outcomes and Benefits: This proposal will provide novel targets and methodology for gene modulation with broad applications from biology to environmental sciences.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE220100964

    Funder
    Australian Research Council
    Funding Amount
    $443,869.00
    Summary
    Statistical approaches for spatial genomics at single cell resolution. Cells cooperate to form complex, dynamic and varied tissue structures. This project aims to develop statistical and computational approaches to analyse spatial genomics data, a novel technology that retains vital spatial information at single cell resolution while detecting RNA molecules for hundreds of genes. Observing the molecular activity of cells in their spatial context is critical for tackling key biological questions, .... Statistical approaches for spatial genomics at single cell resolution. Cells cooperate to form complex, dynamic and varied tissue structures. This project aims to develop statistical and computational approaches to analyse spatial genomics data, a novel technology that retains vital spatial information at single cell resolution while detecting RNA molecules for hundreds of genes. Observing the molecular activity of cells in their spatial context is critical for tackling key biological questions, such as how tumour cells behave during malignancy or how stem cells determine their fate. Expected outcomes also include techniques to fully harmonise spatial and non-spatial genomics datasets, and methods toward understanding the complex relationships among cells in their environment, revealing novel cell biology.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE200100944

    Funder
    Australian Research Council
    Funding Amount
    $427,068.00
    Summary
    Statistical frameworks for high-parameter imaging cytometry data. The project aims to develop statistical and bioinformatics methodology for characterising the complex interactions between cells in their native environment. Recent advances in imaging cytometry technologies have made it possible to observe the behaviour of multiple cell-types in tissue concurrently. The intended outcome is a suite of statistical methodologies that are crucial for addressing a variety of biological problems with t .... Statistical frameworks for high-parameter imaging cytometry data. The project aims to develop statistical and bioinformatics methodology for characterising the complex interactions between cells in their native environment. Recent advances in imaging cytometry technologies have made it possible to observe the behaviour of multiple cell-types in tissue concurrently. The intended outcome is a suite of statistical methodologies that are crucial for addressing a variety of biological problems with these state-of-the-art technologies. This work will advance knowledge in bioinformatics, statistics and image analysis, providing benefits to scientists studying the fundamental behaviour of cells and underlying disease mechanisms.
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    Showing 1-6 of 6 Funded Activites

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