Coupling biophotonic modalities with machine based recognition systems for disease diagnosis. This project will develop new ways to diagnose canine cancer, malaria and atherosclerosis using infrared-based technology and sophisticated pattern recognition techniques in the hope to discover infrared biomarkers that will lead to early diagnosis of the disease and ultimately save lives.
Proteotyping for the rapid identification of pandemic influenza. Future influenza pandemics will develop more rapidly providing a relatively short window with which to survey and assess the nature of the virus and administer effective treatments. Application of a new proteotyping approach will allow strains of pandemic potential to be characterised more directly and rapidly than current surveillance methods.
Predicting the evolution of the influenza virus on mass. Understanding viral reassortment is essential for the development of efficacious vaccines and to prepare for a future influenza pandemic. The research will improve our ability to monitor the evolution of reassorted influenza virus strains using new computer algorithms in concert with the application of bioinformatics and analytical technologies.
Multiscale integration of imaging and omics data. This project aims to integrate multiscale imaging and molecular data to characterise disease in patients. Modern healthcare needs to embrace ‘big (health) data’s potential to address an ageing population’s increasing healthcare demands and the inefficiencies and waste in patient treatment. This project expects to pioneer basic science research in methodologies to integrate, correlate and then derive knowledge from multi-scale data, to characteris ....Multiscale integration of imaging and omics data. This project aims to integrate multiscale imaging and molecular data to characterise disease in patients. Modern healthcare needs to embrace ‘big (health) data’s potential to address an ageing population’s increasing healthcare demands and the inefficiencies and waste in patient treatment. This project expects to pioneer basic science research in methodologies to integrate, correlate and then derive knowledge from multi-scale data, to characterise the mechanisms of disease in individual patients, in space and time. Its integrated model is expected to form the basis of a framework for individualised patient disease analysis.Read moreRead less
RNA-based analysis for prediction of islet death in diabetes. Death of insulin-producing cells is a common feature in diabetes. Presently, a blood glucose test remains the only blunt instrument to diagnose diabetes. The RNA-based analysis for prediction of islet death in diabetes (RAPID) study links with eight clinical trials to test this newly developed non-invasive assay for predicting diabetes. Early diagnosis will help to reduce diabetic complications in later life.