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.
Multivariate Methods for the Analysis of Microarray Gene-Expression Data with Applications to Cancer Diagnostics. The project will benefit the Australian Society as a whole by developing statistical methodology for the analysis of high-throughput data. In particular, it will develop a novel and easily implemented model for the analysis of correlated and structured data that may be of high dimension. It thus has wide applicability to improving the quality and validity of applied research in most ....Multivariate Methods for the Analysis of Microarray Gene-Expression Data with Applications to Cancer Diagnostics. The project will benefit the Australian Society as a whole by developing statistical methodology for the analysis of high-throughput data. In particular, it will develop a novel and easily implemented model for the analysis of correlated and structured data that may be of high dimension. It thus has wide applicability to improving the quality and validity of applied research in most industries in Australia. More specifically, it is to be applied here to the diagnosis and prognosis of ovarian cancer. This cross-disciplinary project will strengthen Australian researchers' capacity and capability of participating in cutting-edge DNA microarray research.
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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
Vertically integrated statistical modelling in multi-layered omics studies. This project will develop an adaptive statistical modelling framework that uses information from many omics data to discover a collection of stable and clinically significant biomarkers. Results will enable researchers to better understand the underlying biological system of complex diseases such as cancer, Alzheimer and diabetes.
Nonparametric data analysis in statistical science. Changes in technology have enabled new types of data to be collected, often more complex and in much larger quantities than ever before, and altered fundamentally the types of questions that need to be asked of those data. The research program will develop new statistical methods for analysing new types of data, for example functional data and data with many dimensions, and will also introduce greatly improved solutions to problems that involve ....Nonparametric data analysis in statistical science. Changes in technology have enabled new types of data to be collected, often more complex and in much larger quantities than ever before, and altered fundamentally the types of questions that need to be asked of those data. The research program will develop new statistical methods for analysing new types of data, for example functional data and data with many dimensions, and will also introduce greatly improved solutions to problems that involve more conventional data types. These techniques will have critical applications to diverse fields. The program will contribute substantially to capacity building in a strategically important area, statistical science, of great value to Australia but where chronic skills shortages exist.Read moreRead less
Prognosis based network-type feature extraction for complex biological data. This project aims to develop statistical tools that integrate high-throughput molecular data with biological knowledge to make discoveries in complex diseases. This project uses machine learning methods, statistical models and proteomic platforms to identify relationships among clinico-pathologic and molecular measurements. It will produce tools and insights that are intended to accelerate the process of biologically an ....Prognosis based network-type feature extraction for complex biological data. This project aims to develop statistical tools that integrate high-throughput molecular data with biological knowledge to make discoveries in complex diseases. This project uses machine learning methods, statistical models and proteomic platforms to identify relationships among clinico-pathologic and molecular measurements. It will produce tools and insights that are intended to accelerate the process of biologically and clinically significant discoveries in biomedical research. This project will help Australian researchers in statistics and users of statistics (from fields as diverse as biology, ecology, medicine, finance, agriculture and the social sciences) to make better predictions that are easier to understand.Read moreRead less
Stochastic populations: theory and applications. The project aims to study models of evolution and cancer development. It will produce new mathematical results and open up new applications of advanced modern mathematical analysis that can be used by evolutionary biologists and cancer researchers, in particular for the understanding of radiation on cell motility.