Identification Of Glaucoma Susceptibility Variants By Exome Sequencing In Extended Pedigrees Showing Prior Evidence Of Gene Segregation.
Funder
National Health and Medical Research Council
Funding Amount
$694,002.00
Summary
Primary open angle glaucoma is a chronic eye disease and one of the leading causes of visual impairment and blindness worldwide. This study will use cutting-edge genetic methods to look at the entire coding component of the human genome (exome) in 271 individuals from large glaucoma families. Our previous studies have shown that these families carry genetic variants that increase disease risk. In this investigation we aim to identify these genes, with the hope they may offer novel targets for tr ....Primary open angle glaucoma is a chronic eye disease and one of the leading causes of visual impairment and blindness worldwide. This study will use cutting-edge genetic methods to look at the entire coding component of the human genome (exome) in 271 individuals from large glaucoma families. Our previous studies have shown that these families carry genetic variants that increase disease risk. In this investigation we aim to identify these genes, with the hope they may offer novel targets for treatment or diagnosis.Read moreRead less
Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data ar ....Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data are needed. This project will design, implement and evaluate visualisation methods for massive multivariate network data sets. This research is expected to be used by Australian software development, biotechnology and security companies to exploit their data.Read moreRead less