Discovery Early Career Researcher Award - Grant ID: DE200100425
Funder
Australian Research Council
Funding Amount
$409,364.00
Summary
Genetic and Molecular Consequences of Non-Random Mating in Humans. This project aims to develop and apply novel statistical methods to quantify the effects on a large number of complex traits of two forms of non-random mating in humans, that is inbreeding and assortative mating. The innovation in this proposal lies in integrating multi-level phenotypes with next-generation sequencing data collected in more than half a million study participants. Expected outcomes of this research include advance ....Genetic and Molecular Consequences of Non-Random Mating in Humans. This project aims to develop and apply novel statistical methods to quantify the effects on a large number of complex traits of two forms of non-random mating in humans, that is inbreeding and assortative mating. The innovation in this proposal lies in integrating multi-level phenotypes with next-generation sequencing data collected in more than half a million study participants. Expected outcomes of this research include advanced analytical methods to perform this integration and dissection of the biological consequences of non-random mating in humans at an unprecedented phenotypically detailed scale. The benefit of this project will be to identify new drivers of mate choice that can contribute to economic, health and social inequalities. Read moreRead less
An intelligent maintenance decision system for the water utility industry. The reliability and maintenance of pump stations is of paramount importance to the water utility industries. In Australia, the maintenance of assets for the water and wastewater industry amounts to $927m per annum. This research will develop an intelligent maintenance decision support system to reduce maintenance costs in pumping stations with increased reliability. The outcomes of the research will significantly improve ....An intelligent maintenance decision system for the water utility industry. The reliability and maintenance of pump stations is of paramount importance to the water utility industries. In Australia, the maintenance of assets for the water and wastewater industry amounts to $927m per annum. This research will develop an intelligent maintenance decision support system to reduce maintenance costs in pumping stations with increased reliability. The outcomes of the research will significantly improve the reliability and supply security of water systems to Queensland's rural and regional communities and industries. It will also advance the body of knowledge of the field of integrated asset management and enhance Australia's international standing in this field.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.
Read moreRead less
On-line and Incremental EM-based Neural Networks: Application to Hospital Utlilization and Gene Expression Data. Artificial neural networks have been widely applied as universal classifiers in many fields, such as biomedicine. However, misunderstanding of fundamental statistical principles, which can cause misleading findings, has been frequently observed in the literature. This project aims to integrate statistical methodologies in neural networks to provide a unified approach to improve its ....On-line and Incremental EM-based Neural Networks: Application to Hospital Utlilization and Gene Expression Data. Artificial neural networks have been widely applied as universal classifiers in many fields, such as biomedicine. However, misunderstanding of fundamental statistical principles, which can cause misleading findings, has been frequently observed in the literature. This project aims to integrate statistical methodologies in neural networks to provide a unified approach to improve its applicability and efficiency in implementation. The system developed from this proposed cross-disciplinary research will be applied to hospital utilization data (hospital morbidity database, Western Australia) and gene expression data (DNA microarrays databases, Harvard University). This collaborative research will advance the international standard of Australian research communities.
Read moreRead less