Research Grant
[Cite as https://purl.org/au-research/grants/arc/DP170100654]Researchers: A/Prof Pengyi Yang (Chief Investigator) , Graham Mann (Chief Investigator) , Jean Yang (Chief Investigator) , John Ormerod (Chief Investigator) , Samuel Muller (Chief Investigator)
Brief description 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.
Funding Amount $354,500
Funding Scheme Discovery Projects
- PURL : https://purl.org/au-research/grants/arc/DP170100654
- ARC : DP170100654