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Australian State/Territory : QLD
Socio-Economic Objective : Mathematical sciences
Research Topic : gene structure
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  • Funded Activity

    Discovery Projects - Grant ID: DP0879308

    Funder
    Australian Research Council
    Funding Amount
    $250,000.00
    Summary
    Statistical methods for detection of non-coding RNAs in eukaryote genomes. Understanding how eukaryotic cells work is a major goal of 21st century biology. A crucial step will be to catalogue the functional components of eukaryotic genomes. Australian researchers must be involved in this process at an early stage, in order to maximise commercial opportunities, attract quality researchers and position ourselves for further advances. This project will make major contributions to international effo .... Statistical methods for detection of non-coding RNAs in eukaryote genomes. Understanding how eukaryotic cells work is a major goal of 21st century biology. A crucial step will be to catalogue the functional components of eukaryotic genomes. Australian researchers must be involved in this process at an early stage, in order to maximise commercial opportunities, attract quality researchers and position ourselves for further advances. This project will make major contributions to international efforts in this area, via the development of statistical methods for segmenting genomes, classification of those segments, and study of the resulting classes. In the long term, enhanced understanding of eukaryotic cells will lead to breakthroughs in biology, and to medical, pharmaceutical, agricultural and scientific advances.
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    Funded Activity

    Discovery Projects - Grant ID: DP0208534

    Funder
    Australian Research Council
    Funding Amount
    $465,483.00
    Summary
    Mutagenesis and combinatorial algorithms for sequencing problematic genomic regions. This project will develop a remarkable and original approach to DNA sequencing with potential to radically improve the speed, accuracy and effectiveness of existing sequencing technologies. It is especially useful for dealing with difficult-to-sequence genomic regions and has implications for all sequencing projects, including completion of the Human Genome Project. The approach involves generating, and wholly o .... Mutagenesis and combinatorial algorithms for sequencing problematic genomic regions. This project will develop a remarkable and original approach to DNA sequencing with potential to radically improve the speed, accuracy and effectiveness of existing sequencing technologies. It is especially useful for dealing with difficult-to-sequence genomic regions and has implications for all sequencing projects, including completion of the Human Genome Project. The approach involves generating, and wholly or partially sequencing, mutated copies of problematic regions of the target genome. Advanced combinatorial algorithms are then used to form highly probable alignments between strings and determine the unknown sequence. The approach has additional benefits in detecting single-nucleotide polymorphisms and sequencing errors.
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    Funded Activity

    ARC Centres Of Excellence - Grant ID: CE0348221

    Funder
    Australian Research Council
    Funding Amount
    $7,260,835.00
    Summary
    ARC Centre in Bioinformatics. The Australian Centre for Genome-Phenome Bioinformatics will examine how the genome comes to life in the mammalian cell during differentiation and development. We will model, visualise and experimentally validate the complex cellular systems and regulatory networks that control the transformation of genomic information into biological structure and function. We will develop novel approaches and tools to improve health, optimise agricultural production and exploit ne .... ARC Centre in Bioinformatics. The Australian Centre for Genome-Phenome Bioinformatics will examine how the genome comes to life in the mammalian cell during differentiation and development. We will model, visualise and experimentally validate the complex cellular systems and regulatory networks that control the transformation of genomic information into biological structure and function. We will develop novel approaches and tools to improve health, optimise agricultural production and exploit new cell technologies. The Centre will build critical mass and national focus in bioinformatics to generate the human capital and intellectual property that Australia needs to compete in advanced bioscience and biotechnology.
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    Funded Activity

    Discovery Projects - Grant ID: DP0344970

    Funder
    Australian Research Council
    Funding Amount
    $126,900.00
    Summary
    Classification of Microarray Gene-Expression Data. The broad aim is to provide statistical methodology for the classification of microarray gene-expression data. Microarrays are part of a new biotechnology that allows the monitoring of expression levels for thousands of genes simultaneously. The explosion in microarrays has produced massive quantities of data that require new statistical techniques for analysis in order to exploit their enormous scientific potential. One of the main uses of .... Classification of Microarray Gene-Expression Data. The broad aim is to provide statistical methodology for the classification of microarray gene-expression data. Microarrays are part of a new biotechnology that allows the monitoring of expression levels for thousands of genes simultaneously. The explosion in microarrays has produced massive quantities of data that require new statistical techniques for analysis in order to exploit their enormous scientific potential. One of the main uses of the methodology to be developed is to expedite the discovery of new subclasses of diseases. Another is to provide prediction rules for the diagnosis and treatment of diseases.
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    Funded Activity

    Linkage Projects - Grant ID: LP0455483

    Funder
    Australian Research Council
    Funding Amount
    $47,112.00
    Summary
    Mining venture risk: novel econometric methods to integrate joint financial and geological uncertainty into dynamic risk forecasting measures. The mining industry is nationally important: it contributed $33,927M to Australia's GDP in 2002-3. This project's outcomes - sophisticated statistical and econometric tools - will significantly improve capability for forecasting overall risk to mining projects requiring vast upfront, irreversible investments, and contribute to its efficiency and internati .... Mining venture risk: novel econometric methods to integrate joint financial and geological uncertainty into dynamic risk forecasting measures. The mining industry is nationally important: it contributed $33,927M to Australia's GDP in 2002-3. This project's outcomes - sophisticated statistical and econometric tools - will significantly improve capability for forecasting overall risk to mining projects requiring vast upfront, irreversible investments, and contribute to its efficiency and international competitiveness. Innovative methods driven by data from complex financial and geological systems will integrate price volatility risk and orebody uncertainty in a real options framework, providing holistic, rigorous measurement of mining venture risk. Xstrata Queensland Ltd will strongly support and participate in research training of an identified candidate to deliver discoveries to the wider industry.
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    Funded Activity

    Discovery Projects - Grant ID: DP1095849

    Funder
    Australian Research Council
    Funding Amount
    $180,000.00
    Summary
    Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identi .... Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identifying RNA molecules that contribute to quantitative phenotypes including susceptibility to disease. As such, it will directly benefit fundamental science via the discovery and classification of new molecules. Indirectly, it will lead to breakthroughs in biology, and consequently to major medical and pharmaceutical advances in the diagnosis and treatment of genetic disease.
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