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Australian State/Territory : QLD
Status : Active
Research Topic : Microarray Bioinformatics
Australian State/Territory : VIC
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP180101334

    Funder
    Australian Research Council
    Funding Amount
    $619,000.00
    Summary
    Next-generation genomic resources to tackle parasitic diseases of animals. The revolution in genomics provides unprecedented opportunities to tackle destructive parasitic diseases affecting billions of animals worldwide. Through a synergy of leading-edge technologies and a strong partnership with BGI International, this project aims to deliver major conceptual advances in the understanding of parasitism; an unparalleled skills-base in genomics and bioinformatics; innovative new molecular technol .... Next-generation genomic resources to tackle parasitic diseases of animals. The revolution in genomics provides unprecedented opportunities to tackle destructive parasitic diseases affecting billions of animals worldwide. Through a synergy of leading-edge technologies and a strong partnership with BGI International, this project aims to deliver major conceptual advances in the understanding of parasitism; an unparalleled skills-base in genomics and bioinformatics; innovative new molecular technologies; and new treatments and diagnostic tests as biotechnological outcomes. This leap forward in Australia will substantially enhance the global profile of parasitology research, training and employment opportunities for early career scientists, and improve access to international research funding and networks.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP180102727

    Funder
    Australian Research Council
    Funding Amount
    $438,211.00
    Summary
    Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising ap .... Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising approach, but its accuracy is far from satisfactory. The software systems developed in this project will be used in structural identification of target proteins in drug design. This will make drug design process more efficient, saving time and cost, potentially saving lives.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP230101352

    Funder
    Australian Research Council
    Funding Amount
    $541,818.00
    Summary
    Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statis .... Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statistical methods provide the opportunity to close this gap. The outcome will be identification of many genomic variants causing variation in complex traits. This will benefit scientific understanding of complex traits and the ability to predict traits for individuals from their genome sequence.
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