Information theoretic approaches to optimise genome wide association studies with application to continuous and discrete traits. This project aims to develop new mathematical methods to find genetic associations from new genome-wide studies of colorectal cancer and breast cancer risk factors. If successful, this will result in improved use of expensive genetic data to better predict and understand diseases, conditions and other characteristics for humans, animals and plants.
Complexity Constrained Iterative Information Processing. The contribution of Information and Communications Technologies to the National Economy has been widely recognized. ICT enables wealth creation, employment and exports, and underpins many innovation processes. Immediate project benefits will be: Contribution to the knowledge base and fundamental capabilities in high-speed wireless communications networks; Education of future Australian academic and industrial innovators; Raising the inter ....Complexity Constrained Iterative Information Processing. The contribution of Information and Communications Technologies to the National Economy has been widely recognized. ICT enables wealth creation, employment and exports, and underpins many innovation processes. Immediate project benefits will be: Contribution to the knowledge base and fundamental capabilities in high-speed wireless communications networks; Education of future Australian academic and industrial innovators; Raising the international profile of Australian research in the area of information technology. Applied development of the outcomes will lead to the generation of valuable intellectual property. Close links to Australian industry ensures that Australian ICT companies stand to gain commercial advantage.Read moreRead less
Generalised Linear Mixed Models: Theory, Methods and New Areas of Application. This project will aid the analysis of complex data sets throughout Australia. The ensuing methodology and software products will be applicable to data arising from longitudinal and geo-referenced public health and biomedical studies being conducted in Australia. It will also aid analysis of complex survey data from the Australian Bureau of Statistics and other agencies. Part of this project is geared towards smart inf ....Generalised Linear Mixed Models: Theory, Methods and New Areas of Application. This project will aid the analysis of complex data sets throughout Australia. The ensuing methodology and software products will be applicable to data arising from longitudinal and geo-referenced public health and biomedical studies being conducted in Australia. It will also aid analysis of complex survey data from the Australian Bureau of Statistics and other agencies. Part of this project is geared towards smart information use in Australian industries and will help foster collaboration between mathematical scientists and members of the Australian business sector. Cancer research in Australia will also benefit from this project.Read moreRead less
Iterative Architechtures for Data Communications. Growing markets for data intensive applications such as real-time video or speech necessitate continual improvements of communications systems. Iterative information processing algorithms have recently received attention for communications equipment design, however theoretical understanding of these methods is still lacking. Within an iterative processing paradigm, the project aim is the optimization of complex communications systems subject to c ....Iterative Architechtures for Data Communications. Growing markets for data intensive applications such as real-time video or speech necessitate continual improvements of communications systems. Iterative information processing algorithms have recently received attention for communications equipment design, however theoretical understanding of these methods is still lacking. Within an iterative processing paradigm, the project aim is the optimization of complex communications systems subject to constraints on computational complexity. Theoretical analysis and design methodologies for such systems will be developed, resulting in basic contributions to statistical science and in cheaper communications infrastructures supporting a wider range of services through better use of limited bandwidth, power and computational complexity.Read moreRead less
Statistical Methods for Flow Cytometric Data. The project will aid users of flow cytometry throughout Australia. It will help foster collaborations between the biological and mathematical scientists. Biological research is an important part of Australia's future and is becoming very quantitative. During the course of the project, two PhD students will be provided strong training in Statistics geared towards biological applications. The project is aligned with the 8th Human Leucocyte Differentiat ....Statistical Methods for Flow Cytometric Data. The project will aid users of flow cytometry throughout Australia. It will help foster collaborations between the biological and mathematical scientists. Biological research is an important part of Australia's future and is becoming very quantitative. During the course of the project, two PhD students will be provided strong training in Statistics geared towards biological applications. The project is aligned with the 8th Human Leucocyte Differentiation Antigen workshop to culminate in Adelaide in December 2004 and will aid the fight against blood cell cancers. The project will also aid research on plankton with potential commercial benefits for Australia's marine scallop industry.
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Advanced Mixture Models for the Analysis of Modern-Day Data. Extracting key information from huge data sets is critical to the scientific successes of the future. This project will develop novel mixture models that can be used directly to analyse complex and high-dimensional data sets that may consist of thousands of variables observed on only a limited number of entities. In order to handle the challenging problems arising in the latter situation. This project develops mixtures of factor models ....Advanced Mixture Models for the Analysis of Modern-Day Data. Extracting key information from huge data sets is critical to the scientific successes of the future. This project will develop novel mixture models that can be used directly to analyse complex and high-dimensional data sets that may consist of thousands of variables observed on only a limited number of entities. In order to handle the challenging problems arising in the latter situation. This project develops mixtures of factor models with options for skew distributions that can be used to effectively analyse such data. Key applications include the domains of bioinformatics, biostatistics, business, data mining, economics, finance, image analysis, marketing, and personalised medicine, among many others.Read moreRead less
Joint clustering and matching of multivariate samples across objects. The project will provide a novel and very effective approach to the clustering of multivariate samples on objects, say patients, that automatically matches the sample clusters across the objects. A key application is the matching of biologically relevant cell subtypes across patients for use in the study and the clinical diagnosis and prognosis of cancer.
Expanding the role of mixture models in statistical analyses of big data. This project aims to develop theoretical procedures to scale inference and learning algorithms to analyse big data sets. It will develop analytic tools and algorithms to analyse big data sets which classical methods of inference cannot analyse directly due to the data’s complexity or size. This will accelerate the progress of scientific discovery and innovation, leading, for example, to new fields of inquiry; to an increas ....Expanding the role of mixture models in statistical analyses of big data. This project aims to develop theoretical procedures to scale inference and learning algorithms to analyse big data sets. It will develop analytic tools and algorithms to analyse big data sets which classical methods of inference cannot analyse directly due to the data’s complexity or size. This will accelerate the progress of scientific discovery and innovation, leading, for example, to new fields of inquiry; to an increase in understanding from studies on human and social processes and interactions; and to the promotion of economic growth and improved health and quality of life. Such applications should lead to breakthrough discoveries and innovation in science, engineering, medicine, commerce, education and national security.Read moreRead less
A new approach to fast matrix factorization for the statistical analysis of high-dimensional data. Some form of dimension reduction is essential in order to extract meaningful information from huge data sets. For this purpose we provide a novel and very fast approach to the factorization of the data matrix. It has wide applicability for improving the quality and validity of research in science and medicine and in most industries in Australia.
Large-Scale Statistical Inference: Multiple Testing. Multiple testing procedures are among the most important statistical tools for the analysis of modern data. This project aims to develop new methods for providing more powerful simultaneous tests while controlling the proportion of false positive conclusions. They are proposed to be derived by the novel pooling of information in individual attribute based contrasts to produce a Weighted Individual attribute-Specific Contrast (WISC) based stati ....Large-Scale Statistical Inference: Multiple Testing. Multiple testing procedures are among the most important statistical tools for the analysis of modern data. This project aims to develop new methods for providing more powerful simultaneous tests while controlling the proportion of false positive conclusions. They are proposed to be derived by the novel pooling of information in individual attribute based contrasts to produce a Weighted Individual attribute-Specific Contrast (WISC) based statistic. They will also exploit contextual information. They are expected to be of direct application to the problem of testing for no differences between two or more classes, as in the detection of differential expression in bioinformatics. Other key applications are expected to include biomedicine, economics, finance, genetics, and neuroscience.Read moreRead less