RNA-binding proteins rewire transcriptomes in immune cell differentiation. This project aims to combine advanced computational and experimental techniques to investigate a new layer of gene regulation by novel RNA binding proteins (RBP) which control messenger RNA length in immune cells. This project expects to demonstrate that these RBPs have a profound effect on immune cell differentiation and response to infection. Expected outcomes include the discovery of new RBPs regulating immunity, with ....RNA-binding proteins rewire transcriptomes in immune cell differentiation. This project aims to combine advanced computational and experimental techniques to investigate a new layer of gene regulation by novel RNA binding proteins (RBP) which control messenger RNA length in immune cells. This project expects to demonstrate that these RBPs have a profound effect on immune cell differentiation and response to infection. Expected outcomes include the discovery of new RBPs regulating immunity, with mechanism and function determined by novel CRISPR editing of a transgenic mouse model. The significant benefit will be a more complete understanding of RNA mechanisms of immune response, which will be critical in informing future advances in the rapidly developing areas of RNA-based biotechnologies and synthetic immunology.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