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.Read moreRead less
Statistical methods and tools for integrative microarray analysis. Tools used for biological and medical research have been evolving and there has been an increase in high-throughput technologies such as genome sequencing and DNA microarray. The growing number of entries and the increasing availability of public microarray repositories and other sequence databases have generated the new challenge of developing tools to efficiently integrate data by different research groups. This research provi ....Statistical methods and tools for integrative microarray analysis. Tools used for biological and medical research have been evolving and there has been an increase in high-throughput technologies such as genome sequencing and DNA microarray. The growing number of entries and the increasing availability of public microarray repositories and other sequence databases have generated the new challenge of developing tools to efficiently integrate data by different research groups. This research provides new statistical methods to integrate different data sets. Its application in the biomedical field will allow researchers to effectively interpret the myriad of data generated within the community.Read moreRead less
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.Read moreRead less
Parameterized Algorithm Design and Complexity Analysis: New Methods and Strategic Applications in the FPT Algorithmic Server Project. A fundamental discovery of the first decades of computer science is that completely efficient (polynomial time) algorithms probably do not exist for thousands of natural computational problems. The project will result in new methods for designing and analyzing algorithms for hard problems with natural parameters, and in improved
algorithms for these problems.
A new theory for retinotectal map formation. How brains become wired up during development is a question of
importance to both biology and computing. In this project we adopt a
novel computational approach to understanding the development of
topographic maps, a wiring pattern that is ubiquitous in biological
nervous systems. This project will build capacity for research in
computational neuroscience in Australia. It may also lead to
technological benefits such as new ideas for the design o ....A new theory for retinotectal map formation. How brains become wired up during development is a question of
importance to both biology and computing. In this project we adopt a
novel computational approach to understanding the development of
topographic maps, a wiring pattern that is ubiquitous in biological
nervous systems. This project will build capacity for research in
computational neuroscience in Australia. It may also lead to
technological benefits such as new ideas for the design of self-wiring
computing devices, and new insights into
the causes of wiring defects both during normal development and
rewiring after injury.
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Wiring up the nervous system: how do axons detect molecular gradients? This project will improve our understanding of how the nervous system
becomes wired up during development. This will ultimately allow better
therapies for some types of developmental disorders, and for repairing
damaged connections for instance in the spinal cord. The theoretical
models developed will improve our understanding of the computations
necessary to generate appropriate wiring of the nervous system, which
may ....Wiring up the nervous system: how do axons detect molecular gradients? This project will improve our understanding of how the nervous system
becomes wired up during development. This will ultimately allow better
therapies for some types of developmental disorders, and for repairing
damaged connections for instance in the spinal cord. The theoretical
models developed will improve our understanding of the computations
necessary to generate appropriate wiring of the nervous system, which
may facilitate the development of self-organizing computing
devices. The project will also provide unique research training at the
interface of biology and computation, building capacity for such
interdisciplinary research throughout Australia.
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Evolutionary multi-objective algorithms for Global Grids. This research investigates alternative software technologies for Grid-based evolutionary multi-objective decision algorithms. By employing the latest adaptive techniques and taking advantage of the low cost Grid infrastructure, new parallel evolutionary systems will be developed that can rapidly supply robust solutions to complex problems. This project will further develop an understanding of scaling issues in parallel evolutionary syste ....Evolutionary multi-objective algorithms for Global Grids. This research investigates alternative software technologies for Grid-based evolutionary multi-objective decision algorithms. By employing the latest adaptive techniques and taking advantage of the low cost Grid infrastructure, new parallel evolutionary systems will be developed that can rapidly supply robust solutions to complex problems. This project will further develop an understanding of scaling issues in parallel evolutionary systems and pave the way for even more widespread application of evolutionary techniques for large scale, data-intensive applications in science and industry.Read moreRead less
Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discove ....Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discovery and validation of group structure in data mining applications will considerably enhance knowledge management and decision support in science, industry, and government.
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Realising the promise of neural networks for practical optimisation: improving their efficiency and effectivess through chaotic dynamics and hardware implementation. Combinatorial optimisation problems such as transportation routing and assembly-line scheduling are critical to the efficiency of many industries, but their combinatorial explosion makes rapid solution difficult. Neural networks (NNs) hold much potential for rapid solution though hardware implementation, but we need to improve the q ....Realising the promise of neural networks for practical optimisation: improving their efficiency and effectivess through chaotic dynamics and hardware implementation. Combinatorial optimisation problems such as transportation routing and assembly-line scheduling are critical to the efficiency of many industries, but their combinatorial explosion makes rapid solution difficult. Neural networks (NNs) hold much potential for rapid solution though hardware implementation, but we need to improve the quality of their solutions before developing hardware. We have previously shown that the rich dynamics of chaos can improve the efficiency and effectiveness of NNs. We aim to develop new chaotic NN models, rigorously evaluate them on industrially significant problems such as those arising in manufacturing, logistics and telecommunications, and demonstrate their speed through hardware acceleration.Read moreRead less