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Research Topic : host/pathogen interaction
Australian State/Territory : NSW
Field of Research : Software Engineering
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  • Funded Activity

    Discovery Projects - Grant ID: DP0560045

    Funder
    Australian Research Council
    Funding Amount
    $160,000.00
    Summary
    Topological Approaches for Three Dimensional Graph Drawing. Human analysis of huge quantities of relational data in biotechnology, web engineering, social networks, and computer networks requires visualization. In recent years, three-dimensional visualisation has promised to give new insights into such abstract data. However the past ten years of visualization research has had very little impact on the industry; visualization software providers have not adopted visualization methods developed b .... Topological Approaches for Three Dimensional Graph Drawing. Human analysis of huge quantities of relational data in biotechnology, web engineering, social networks, and computer networks requires visualization. In recent years, three-dimensional visualisation has promised to give new insights into such abstract data. However the past ten years of visualization research has had very little impact on the industry; visualization software providers have not adopted visualization methods developed by academics. We hypothesise that current 3D relational visualization methods fail because they do not pay attention to the human perception of topology. In this project we will leverage mathematical topology to construct new methods for the 3D visualization of relational data.
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    Funded Activity

    Linkage Projects - Grant ID: LP0455334

    Funder
    Australian Research Council
    Funding Amount
    $70,668.00
    Summary
    New Methods for Interactive Visualization of Large Microarray Data Sets. This project will investigate methods for visualising graphs produced by AI-based analysis of real-world biological data. These new visualisation methods will assist biologists to develop new DNA Microarray experiments, the source of raw data for visualisation. Data from new enhanced experiments, plus background knowledge from integrated public databases will produce richer data for visualisation, thus creating a positive f .... New Methods for Interactive Visualization of Large Microarray Data Sets. This project will investigate methods for visualising graphs produced by AI-based analysis of real-world biological data. These new visualisation methods will assist biologists to develop new DNA Microarray experiments, the source of raw data for visualisation. Data from new enhanced experiments, plus background knowledge from integrated public databases will produce richer data for visualisation, thus creating a positive feedback loop in the course of research into both topics.
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    Funded Activity

    Linkage Projects - Grant ID: LP160100935

    Funder
    Australian Research Council
    Funding Amount
    $382,000.00
    Summary
    Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data ar .... Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data are needed. This project will design, implement and evaluate visualisation methods for massive multivariate network data sets. This research is expected to be used by Australian software development, biotechnology and security companies to exploit their data.
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