Pharmacology Of Potential Anti-Tumour Agents: Iron Chelators Of The BpT Class
Funder
National Health and Medical Research Council
Funding Amount
$585,455.00
Summary
Pharmacology of Potential Anti-Tumour Agents: Iron Chelators of the BpT Class Cancer cells have a high iron requirement for DNA synthesis and many clinical trials showed Fe chelators are effective anti-cancer drugs. Their potential to act as anti-tumour agents has been confirmed by the entrance of Triapine into widespread NCI clinical trials. In this NHMRC Renewal, we will perform pharmacological and preclinical studies to promote the development of BpT chelators as novel anti-tumour agents.
Design of dynamic visual signals. Models of the design of visual signals depend heavily upon analyses of static ornaments. Nothing is known about dynamic visual signals. We will use an array of new techniques to tackle this problem for the first time. Motion analyses will define the task faced by the visual system. Sensory limitations will be measured to identify constraints on signal evolution. Digital video playback studies will assess recognition and explain aspects of signal design. Results ....Design of dynamic visual signals. Models of the design of visual signals depend heavily upon analyses of static ornaments. Nothing is known about dynamic visual signals. We will use an array of new techniques to tackle this problem for the first time. Motion analyses will define the task faced by the visual system. Sensory limitations will be measured to identify constraints on signal evolution. Digital video playback studies will assess recognition and explain aspects of signal design. Results will test the generality of principles that have been developed in studies of female mate choice and extend these ideas to address intra-sexual selection operating through opponent assessment.Read moreRead less
Machine education for trusted multi-skilled evolutionary learners . Transforming data assets into organisational knowledge assets sits in the hands of a few, highly specialised, data scientists. The aim of this research is to design educational instruments to support non-experts to teach artificial intelligence (AI) systems in a similar way to educating human teachers to teach human learners. The significance of the project lies in affording the wider smart, but not necessarily AI expert, commun ....Machine education for trusted multi-skilled evolutionary learners . Transforming data assets into organisational knowledge assets sits in the hands of a few, highly specialised, data scientists. The aim of this research is to design educational instruments to support non-experts to teach artificial intelligence (AI) systems in a similar way to educating human teachers to teach human learners. The significance of the project lies in affording the wider smart, but not necessarily AI expert, community the ability to contribute to growing our knowledge-based society in a safe, transparent and trustworthy manner. Outcomes will include innovative instruments to teach machines, novel knowledge creation, trusted and transparent AI systems, and a new generation of human teachers specialised in educating AI systems.Read moreRead less
User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating conc ....User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating concepts, designs, products and advanced training systems in industry and government organisations. By bringing the user naturally inside the simulation as a task's component, users can improve their experience while task performance is simultaneously optimised. Intended outcomes include novel dynamic user-task profiling algorithms and new adaptive algorithms for user-task co-adaptation. Practical outcomes may include robust and highly effective simulation environments.Read moreRead less
ADAM Metalloprotease Inhibition For Treatment Of Colorectal Cancer
Funder
National Health and Medical Research Council
Funding Amount
$770,925.00
Summary
Colorectal cancer (CRC) causes over 4000 deaths/year, typically from developing drug resistance and spreading to other organs (metastasis). These processes involve tumour cells called cancer stem cells (CSCs), which rely on specific cell surface proteins for survival and function. We are developing antibodies against one of these type of proteins, to test in mouse models of CRC. These already show promise in targeting CSCs and inhibiting drug-resistance and metastasis in mice.
The Role And Inheritance Of Constitutional Epimutations In Early-onset Colorectal Cancer.
Funder
National Health and Medical Research Council
Funding Amount
$347,551.00
Summary
Traditionally familial cancers are thought to be caused by spelling mistakes within the genetic code of cancer prevention genes. Our group has found that chemical attachments to one gene (MLH1) stops it working, even where there is no spelling mistake, and that those chemical changes can be inherited in families with bowel cancer. We will determine how frequently this type of defect occurs in bowel cancer patients, how and why it arises, and if other cancer genes are similarly affected.
Discovery of novel microRNA biogenesis and functional components. Discovery of novel microRNA components will provide new strategies for confronting a diverse array of challenges Australia faces, such as the increasing rates of certain cancers in our population, to stresses on our crop plants faced with environmental changes. The biological mechanisms underlying these disparate problems are unified by microRNA involvement in many instances. By finding microRNA controlling factors common to all h ....Discovery of novel microRNA biogenesis and functional components. Discovery of novel microRNA components will provide new strategies for confronting a diverse array of challenges Australia faces, such as the increasing rates of certain cancers in our population, to stresses on our crop plants faced with environmental changes. The biological mechanisms underlying these disparate problems are unified by microRNA involvement in many instances. By finding microRNA controlling factors common to all higher organisms, we expect our community will benefit from the increased knowledge base that will help our researchers adopt new strategies in fighting diseases and improving our agricultural industry.Read moreRead less
Evolutionary computation for expensive bilevel multiobjective problems. This project aims to develop an evolutionary computation framework to solve computationally expensive bilevel multiobjective problems. The research is fundamental in nature and will address key open challenges in solving such problems, including hierarchical decision-making, multiple performance criteria, uncertainties and computational expense. The proposed research has applications in diverse domains such as environmental ....Evolutionary computation for expensive bilevel multiobjective problems. This project aims to develop an evolutionary computation framework to solve computationally expensive bilevel multiobjective problems. The research is fundamental in nature and will address key open challenges in solving such problems, including hierarchical decision-making, multiple performance criteria, uncertainties and computational expense. The proposed research has applications in diverse domains such as environmental policy formulation, network design, engineering, defence and cybersecurity; offering significant benefits to the researchers and practitioners in these fields. In addition to research outputs, it will strengthen international collaboration and build research capacity to put Australia at the forefront of this research.
Read moreRead less
Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learnin ....Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learning of the syntax and semantics of individual gestures and actions, nor the multi-gesture information fusion required for understanding, which could significantly enhance efficiency, for example, in sorting through named entities in an investigation. All of this is done naturally by most human beings, using biological neural networks.Read moreRead less
Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algori ....Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algorithms with the aim of designing algorithms better able to exploit prior knowledge, and to extend existing algorithms to new problem domains thus offering well principled and well understood algorithms for solving a variety of novel online problems.Read moreRead less