Simulating viral evolution and genetic complexity. This project has direct relevance to understanding the growth of viral infections, and therefore has possible practical applications in disease research and control. Examples of these are emerging diseases in humans such as those caused by HIV-1, SARS coronavirus and Dengue virus, which cause considerable human suffering throughout the world. A major part of current research into these diseases involves attempts to model the evolutionary geneti ....Simulating viral evolution and genetic complexity. This project has direct relevance to understanding the growth of viral infections, and therefore has possible practical applications in disease research and control. Examples of these are emerging diseases in humans such as those caused by HIV-1, SARS coronavirus and Dengue virus, which cause considerable human suffering throughout the world. A major part of current research into these diseases involves attempts to model the evolutionary genetics and dynamics of virus populations in order to understand how to control epidemics, develop vaccines and design drugs. The research program is designed to provide new computational modelling tools for this purpose, which may have wider applications as well.
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New nonparametric statistical methods for imperfectly observed data. Statistical science today is facing the challenge of having to answer questions about data that are more complex than ever before. Some of the major difficulties are caused by the lack of direct access to quantities of interest, and the more intricate structure of the available data. Motivated by applications in areas such as cancer and genetic studies, infectious disease, environmental pollution, and public health and nutriti ....New nonparametric statistical methods for imperfectly observed data. Statistical science today is facing the challenge of having to answer questions about data that are more complex than ever before. Some of the major difficulties are caused by the lack of direct access to quantities of interest, and the more intricate structure of the available data. Motivated by applications in areas such as cancer and genetic studies, infectious disease, environmental pollution, and public health and nutrition, this project aims to develop novel and highly effective statistical methodology for solving contemporary problems involving new types of imperfectly observed data. The expected outcomes will solve frontier problems, where information can only be accessed through sophisticated computer intensive methods.Read moreRead less
Statistical challenges involving indirect data. This project aims to develop statistical methodology for solving contemporary problems involving indirectly observed data whose complexity is exacerbated by factors such as incompleteness or episodic availability. Modern statistics find it difficult to analyse complex data which contain important information only in an indirect way, such as data measured with noise or aggregated data. This project considers both finite dimensional data and function ....Statistical challenges involving indirect data. This project aims to develop statistical methodology for solving contemporary problems involving indirectly observed data whose complexity is exacerbated by factors such as incompleteness or episodic availability. Modern statistics find it difficult to analyse complex data which contain important information only in an indirect way, such as data measured with noise or aggregated data. This project considers both finite dimensional data and functional data. The expected methodology will be able to solve frontier problems, where only sophisticated methods can access information. This is expected to benefit brain studies, economics, infectious disease, nutrition and public health.Read moreRead less
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
Modeling Healthcare Systems. An efficient healthcare system is essential for the well-being of any society. The aim of the project is to develop major advances in the mathematical modelling of healthcare systems, in order to improve efficiency, and ultimately, patient health. The first expected outcome is the development of mathematical models that constitute a high-level description of patient flow through hospitals and subacute care, so that demands for emergency and elective capacity are met ....Modeling Healthcare Systems. An efficient healthcare system is essential for the well-being of any society. The aim of the project is to develop major advances in the mathematical modelling of healthcare systems, in order to improve efficiency, and ultimately, patient health. The first expected outcome is the development of mathematical models that constitute a high-level description of patient flow through hospitals and subacute care, so that demands for emergency and elective capacity are met given limited resources. The second is the development of a bed allocation algorithm that allocates patients to appropriate wards, so as to optimise the set of performance indicators of the system under appropriate constraints, given the current ward occupancy.Read moreRead less