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
Decoding miRNA regulated genetic circuits. This project will aim to develop a much better understanding of how the process of making proteins from genes is regulated, and will develop scientific software capable of predicting how a cell will respond to changes in this regulation. The results will have widespread use, including assistance in deciding the best treatments for genetic diseases.
Large-scale Cancer Proteomic Analyses For Improved Prediction Of Drug Response, Patient Prognosis And Clinical Outcome
Funder
National Health and Medical Research Council
Funding Amount
$318,768.00
Summary
Proteomics is the study of all of the proteins encoded by a genome. In this project, I will use a new database of proteomic and clinical data from up to 70,000 cancer samples, and create an approach to correlate proteomic features with drug response, patient prognosis and clinical outcome. The aim of this research will be to use proteomics to better guide treatment decisions, with the potential to significantly improve the health of people with cancer, both in Australia and globally.
Improving Bioinformatic Methods For Studying Gene Regulation In Health And Disease
Funder
National Health and Medical Research Council
Funding Amount
$463,652.00
Summary
New methods for analysing genome-wide data will be developed to ease the data analysis bottleneck that currently exists in medical research. Modelling variation in gene expression from single cells, in screens designed to uncover gene function and assays that measure the factors that turn genes on or off will be the focus. Free software will be developed and made available to researchers worldwide to help them interpret the large and complex data sets that are now routine in genomic medicine.
High-throughput genetic assays are commonly used to study the molecular basis of disease and such technology requires sophisticated data analysis methods that account for significant biological and experimental complexity. Specialized methods will be developed in free public software that will greatly benefit future genetic profiling studies.
Discovering The Genetic Causes Of Congenital Heart Disease Using Systems Biology
Funder
National Health and Medical Research Council
Funding Amount
$419,180.00
Summary
Congenital heart disease (CHD) affects one in one hundred live-born babies, representing a significant health burden in Australia and worldwide. My research team is using state-of-the-art DNA sequencing technology to sequence the entire genome of hundreds of patients with CHD and their family members. My research program develops fast and reliable computer software to accelerate the discovery of the genetic causes of CHD, and make personalised genome-based medicine a reality.
Investigating Widespread Regulation Of Gene Expression Through Intron Retention
Funder
National Health and Medical Research Council
Funding Amount
$363,026.00
Summary
We recently discovered a hidden type of gene regulation that appears to be altered in diverse cancers including leukaemia, melanoma and colon cancer. We will explore this widely relevant mechanism using molecular and computational tools. We created the only computer program able to detect this type of regulation and will now share our discovery with cancer scientists through cloud computing technology.