COMPLEX NETWORKS: DYNAMICS, OPTIMIZATION AND CONTROL. Complex networks such large power grids, the Internet, transportation networks and co-operation networks of all kinds provide challenges for frontier technologies particularly computing, communication and control. In particular, advanced societies have become dependent on large infrastructure networks to an extent beyond our capability to plan and control them. The recent spate of collapses in power grids and virus attacks on the Internet i ....COMPLEX NETWORKS: DYNAMICS, OPTIMIZATION AND CONTROL. Complex networks such large power grids, the Internet, transportation networks and co-operation networks of all kinds provide challenges for frontier technologies particularly computing, communication and control. In particular, advanced societies have become dependent on large infrastructure networks to an extent beyond our capability to plan and control them. The recent spate of collapses in power grids and virus attacks on the Internet illustrate the need for research on modelling, analysis of behaviour, planning and control in such networks. This project aims to establish research in this area for Australia's benefit.Read moreRead less
Dynamics and Security Control of Complex Networks. The research will yield basic techniques to analyse, design and operate complex networks so that security, as well as performance, is achieved. These techniques will be further developed towards particular applications including power grids and telecommunication networks. However, the emphasis is on providing basic ideas and techniques.
Markov invariants and phylogenetic tree reconstruction. The project will assist Australia to progress as an innovator in the production phylogenetic tree reconstruction techniques.
Identifying species is a difficult task with environmental, social and economic benefits to Australia. DNA evidence and phylogenetic methods clearly achieve this task. Conservation of rare species depends upon identification and hence robust phylogenetic analysis. Phylogenetically identifying fish species has econom ....Markov invariants and phylogenetic tree reconstruction. The project will assist Australia to progress as an innovator in the production phylogenetic tree reconstruction techniques.
Identifying species is a difficult task with environmental, social and economic benefits to Australia. DNA evidence and phylogenetic methods clearly achieve this task. Conservation of rare species depends upon identification and hence robust phylogenetic analysis. Phylogenetically identifying fish species has economic importance as different fish species are all managed separately, having different catch limits, catch areas and market values. Using effective phylogenetic methods, epidemiologists can track the spread of a disease through a population. Read moreRead less
Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identi ....Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identifying RNA molecules that contribute to quantitative phenotypes including susceptibility to disease. As such, it will directly benefit fundamental science via the discovery and classification of new molecules. Indirectly, it will lead to breakthroughs in biology, and consequently to major medical and pharmaceutical advances in the diagnosis and treatment of genetic disease.Read moreRead less
Maximizing Dimensional Efficiency With Minimal Cardinality Pattern Combinations. Making optimal use of dimensional capacity is often fundamental to the efficiency of processes in science and industry. Many important applications use combinations of patterns to achieve this. For example, in paper and in steel manufacturing, reels are divided lengthwise into cutting patterns, combined so as to minimize waste. In medicine, radiation patterns are combined to effectively treat cancerous tumours. ....Maximizing Dimensional Efficiency With Minimal Cardinality Pattern Combinations. Making optimal use of dimensional capacity is often fundamental to the efficiency of processes in science and industry. Many important applications use combinations of patterns to achieve this. For example, in paper and in steel manufacturing, reels are divided lengthwise into cutting patterns, combined so as to minimize waste. In medicine, radiation patterns are combined to effectively treat cancerous tumours. By addressing the common mathematical structure underlying pattern combination, this project will account for a hitherto neglected critical factor - the solution cardinality - making fully optimized solutions available for the first time to many applications in science and industry.Read moreRead less
Complex data, model selection and bootstrap inference. The project will provide new statistical methods and associated software for the analysis and modelling of complex data, as well as quality research training. This project will benefit researchers in statistics and users of statistics who encounter the complex data considered in this project and who need to model and make inferences from these data. Since these kinds of data arise in many areas (such as medicine, genetics, chemistry etc), ....Complex data, model selection and bootstrap inference. The project will provide new statistical methods and associated software for the analysis and modelling of complex data, as well as quality research training. This project will benefit researchers in statistics and users of statistics who encounter the complex data considered in this project and who need to model and make inferences from these data. Since these kinds of data arise in many areas (such as medicine, genetics, chemistry etc), Australia and Australian industry will ultimately benefit from the proposed research. The strengthening of international link and the training of highly trained research scientists in an area of national importance will also benefit Australia.Read moreRead less
Innovations in Bayesian likelihood-free inference. Bayesian inference is a statistical method of choice in applied science. This project will develop innovative tools which permit Bayesian inference in problems considered intractable only a few years ago. These methods will expedite advances in multidisciplinary research across a range of applications. With these foundations, this project will accelerate national research efforts into improving frameworks for projecting trends in water availabil ....Innovations in Bayesian likelihood-free inference. Bayesian inference is a statistical method of choice in applied science. This project will develop innovative tools which permit Bayesian inference in problems considered intractable only a few years ago. These methods will expedite advances in multidisciplinary research across a range of applications. With these foundations, this project will accelerate national research efforts into improving frameworks for projecting trends in water availability and management, the impact of climate extremes, telecommunications engineering, HIV and infectious disease modelling and biostatistics. With many sectors unable to recruit appropriately trained statisticians within Australia, this project will train four PhD students in Bayesian statistics.
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Statistical methods for analysing multi-source microarray data and building gene regulatory networks. I will devise a statistical learning technique that does not force a gene to be assigned to exactly one category. This technique reflects the biological reality that a gene can belong to two or more functional categories. Therefore, the new technique will improve a model's ability to identify regulatory genes in different types of cancer; these regulatory genes can be targeted by new anti-cancer ....Statistical methods for analysing multi-source microarray data and building gene regulatory networks. I will devise a statistical learning technique that does not force a gene to be assigned to exactly one category. This technique reflects the biological reality that a gene can belong to two or more functional categories. Therefore, the new technique will improve a model's ability to identify regulatory genes in different types of cancer; these regulatory genes can be targeted by new anti-cancer drugs resulting in a more effective treatment. I will model gene regulatory networks using microarray data from multiple sources. These networks will be used to identify regulatory cliques - a group of genes that are vital for a cellular function. This will improve our understanding of debilitating conditions such as asthma.Read moreRead less
Modelling mean and dispersion using fixed and random effects. The aims of the project are to develop methods for joint mean and dispersion modelling using fixed and random effects, in the generalized linear models context and for Gaussian longitudinal data. The significance is the more efficient, precise and appropriate analysis of data arising from many areas of application. The expected outcomes are therefore better methods of analysis, software to carry the analyses out, and potentially impor ....Modelling mean and dispersion using fixed and random effects. The aims of the project are to develop methods for joint mean and dispersion modelling using fixed and random effects, in the generalized linear models context and for Gaussian longitudinal data. The significance is the more efficient, precise and appropriate analysis of data arising from many areas of application. The expected outcomes are therefore better methods of analysis, software to carry the analyses out, and potentially important results in applications.Read moreRead less
Bootstrap methods for data with multiple errors. This project will provide new methods for data analysis and quality research training. The results will benefit researchers in statistics and users of statistics who encounter data with multiple errors and who need to make inferences from these data. The many areas from which such data arise (including medicine, genetics, chemistry, education, social surveys etc) mean that Australia and Australian Industry will also ultimately benefit from the r ....Bootstrap methods for data with multiple errors. This project will provide new methods for data analysis and quality research training. The results will benefit researchers in statistics and users of statistics who encounter data with multiple errors and who need to make inferences from these data. The many areas from which such data arise (including medicine, genetics, chemistry, education, social surveys etc) mean that Australia and Australian Industry will also ultimately benefit from the research. The strengthening of international links and the training of highly trained researchers will also benefit the Australian community.Read moreRead less