Elucidating The Mechanisms And Consequences Of Clinical HIV-1 Resistance To The CCR5 Antagonist Maraviroc
Funder
National Health and Medical Research Council
Funding Amount
$622,732.00
Summary
CCR5 antagonists are a new class of anti-HIV drug, and maraviroc (MVC) is the only CCR5 antagonists that is licensed for use as a HIV treatment. Like all HIV treatments, drug resistance to MVC can develop in patients. This study will determine the mechanism of how HIV becomes resistant to MVC, which will permit the development of improved, second generation CCR5 antagonists, and will reveal ways to determine which patients are more likely to develop MVC resistance.
Understanding HIV Resistance To Entry Inhibitors To Advance The Development Of Novel Antivirals
Funder
National Health and Medical Research Council
Funding Amount
$877,585.00
Summary
We cannot afford to be complacent in the search for improved anti HIV drugs for 2 principal reasons; First, worldwide a staggering 66% of infected individuals who need treatment are still unable to access therapy; and Second, the main reason why most treated patients are now living longer and more healthy lives is because we have never stopped developing newer therapies to provide options for patients. In this study we will develop and test newer drugs that block HIV infection of cells.
Intrinsic Host Antiviral Activity Against Pathogenic Filoviruses
Funder
National Health and Medical Research Council
Funding Amount
$488,754.00
Summary
Bats are a major reservoir for deadly human viruses including Ebola and Marburg virus. In contrast to humans, bats can be infected with these viruses without showing clinical signs of disease. The reason why bats can co-exist with these viruses is unknown. This study will determine if a bat antiviral molecule contributes to limiting virus release compared to the human version that could reveal strategies to prevent and control these deadly viruses in humans.
Efficient spatial data management for enabling true ride-sharing. This data management project aims to examine ride-sharing as a model of a complex decision system that can be optimised to deliver better outcomes. Popular ride-sharing apps have quickly evolved into ride-sourcing services that are comparable to calling a taxi on a mobile phone. Such arrangements miss many of the key benefits of true ride-sharing for the society. The project will model incentives by helping people agree on points ....Efficient spatial data management for enabling true ride-sharing. This data management project aims to examine ride-sharing as a model of a complex decision system that can be optimised to deliver better outcomes. Popular ride-sharing apps have quickly evolved into ride-sourcing services that are comparable to calling a taxi on a mobile phone. Such arrangements miss many of the key benefits of true ride-sharing for the society. The project will model incentives by helping people agree on points of interest rather than directly seeking trips from others to set destinations. It also aims to introduce privacy-aware dynamic matching of sharers, and expand to transportation at large, to generate new shared transportation services. The expected outcome of this project is to elevate today's taxi-like ride-sharing services to true ride-sharing arrangements. This is expected to provide benefits such as reduced traffic and emissions, as well as addressing parking issues and other traffic problems.Read moreRead less
Next generation data mining techniques for analysing large evolving networks. In order to understand complex systems such as the Internet or gene interactions, we need to analyse how the networks in these systems function and evolve. This project will provide new methods for extracting knowledge from large network databases so that scientists can learn about the operation of these complex systems.
Multi source inference from heterogeneous dynamic networks. Sophisticated big data applications in engineering, the social sciences and biology are now generating flows of data across multiple sources possessing a variety of structures. An emerging challenge is how to develop data mining methods that can cope with this complexity and diversity to make inferences and provide practical insights. This project will develop methods in tensor data mining that provide a new foundation for extracting us ....Multi source inference from heterogeneous dynamic networks. Sophisticated big data applications in engineering, the social sciences and biology are now generating flows of data across multiple sources possessing a variety of structures. An emerging challenge is how to develop data mining methods that can cope with this complexity and diversity to make inferences and provide practical insights. This project will develop methods in tensor data mining that provide a new foundation for extracting useful knowledge from multi source heterogeneous data sets. This will help accelerate discoveries in the next generation of data driven science.Read moreRead less
Personalised data analytics for the Internet of Me. This project aims to develop data mining methods for extracting comprehensive personalised knowledge, without breaching trust. The Internet of Things will lead to the Internet of Me. Billions of smart devices connected to the Internet record people’s lives. Companies wish to provide highly personalised services that engage their customers, while individuals wish to understand their health, lifestyle, education and personal performance. The chal ....Personalised data analytics for the Internet of Me. This project aims to develop data mining methods for extracting comprehensive personalised knowledge, without breaching trust. The Internet of Things will lead to the Internet of Me. Billions of smart devices connected to the Internet record people’s lives. Companies wish to provide highly personalised services that engage their customers, while individuals wish to understand their health, lifestyle, education and personal performance. The challenge is to analyse individuals’ personal data, and discover how they differentiate from and overlap with others’. This project expects to enable businesses to deepen customer satisfaction and individuals to better understand their personal place in a connected world.Read moreRead less
Harnessing Tyrosine Metabolism To Combat Respiratory Diseases
Funder
National Health and Medical Research Council
Funding Amount
$866,467.00
Summary
Cross-talk between our immune system and the microbiome is central to health and disease. In particular, the gut microbiome has wide-ranging effects throughout the body, in part through the production of metabolites with immunomodulatory activity. We have discovered a novel subset of microbial metabolites which can protect mice against allergic airway inflammation, a model of asthma. We now aim to discovery how these metabolites work with a view towards developing them as therapeutics.
Real-time and self-adaptive stream data analyser for intensive care management. The clinical benefit of this project will be in improved success rates and reduced mortality and risk in surgery and intensive care units. The Information and communication technology (ICT) benefit of this project is associated with the novel online algorithms and models aligned with the stream data research, and will be enhanced by our stream compression techniques. The stream data analyser developed in this projec ....Real-time and self-adaptive stream data analyser for intensive care management. The clinical benefit of this project will be in improved success rates and reduced mortality and risk in surgery and intensive care units. The Information and communication technology (ICT) benefit of this project is associated with the novel online algorithms and models aligned with the stream data research, and will be enhanced by our stream compression techniques. The stream data analyser developed in this project will be suitable for more than medical surveillance data; it will also improve the processing of other kinds of massive stream data (for example data from remote sensors, communication networks and other dynamic environments). The project involves a scientifically rich collaboration that will enhance the skills of PhD students and staff and drive the field forward.Read moreRead less