New genomic technologies are revolutionizing biological research. RNA-seq is a recently developed high-throughput sequencing technology that provides scientists with much more detail how genes are regulated and expressed than any earlier technology. New tools developed by Professor Gordon Smyth are allowing researchers to use RNA-Seq technology to more accurately determine which genes are genuinely changing in the development of cancers and in response to cancer treatments.
Binary regression with additive predictors: new statistical theory with healthcare applications. This project will develop new statistical analysis techniques for predicting whether someone is at risk of adverse health outcomes. The project will then apply the new techniques to a large database on heart attacks, leading to new insights into how patient characteristics and treatments affect the chance of dying from a heart attack.
A likelihood-based approach to combined surveys inference. This project focuses on the development of statistical theory for efficient integration of information across multiple complex sample surveys. It will develop theory and methodology that will answer complex questions about relationships between important social, economic and health related variables that are presently measured in separate surveys.
Constructing Control Samples For The Australian And Other Populations: Improving Power And False Positive Rates In The Next Generation Of Genetic Association Studies With A Focus On Controlling For Fine-scale Population Structure In DNA Sequence Data
Funder
National Health and Medical Research Council
Funding Amount
$283,447.00
Summary
Individuals who live near each other tend to be more similar genetically than individuals who live in different parts of the world. One reason is that they share more of their genetic ancestry. There can be very subtle differences in patterns of genetic variation even within countries. Accounting for these subtle differences can be important for studies of the genetic basis of diseases. We will develop novel statistical methods to control for these genetic differences in disease studies.
Automated Screening Measures Associated With Risk And Treatment (SMART) Of Breast Cancer
Funder
National Health and Medical Research Council
Funding Amount
$98,244.00
Summary
Women with greater mammographic density (white area on a mammogram) are at greater risk of breast cancer. Prof Hopper (supervisor) has led international research in this area using a method called CUMULUS. Drs Makalic and Schmidt (co-supervisors) have created an automated measure, called CIRRUS. My aims are to: find out which factors influence CIRRUS, confirm that CIRRUS predicts breast cancer risk, and develop automated measures of a breast cancer risk based on magnetic resonance imaging (MRI).
Revealing How Interactions And Mutation Patterns Among Genes Change In Different Human Tissues By Bioinformatics Tools
Funder
National Health and Medical Research Council
Funding Amount
$334,884.00
Summary
Our understanding of common disease is hampered by the complexity of the human system. The DNA variations found in genome wide association studies of common disease are rarely in the gene coding region. I aim to develop statistical bioinformatic tools to find how the DNA variations affect human disease by taking gene expression as the quantitative phenotype. The results will explain the genetic risk of human common disease, so that better personalized prevention and therapy can be achieved.
Biostatistical Innovation And Capacity Building To Advance Child Health And Life-course Epidemiology
Funder
National Health and Medical Research Council
Funding Amount
$470,144.00
Summary
Biostatistics is a critical component of health and medical research. The proposed program of novel biostatistical research into methods for analysing incomplete data, an extensive portfolio of collaborative research in infant development, and establishment of a national biostatistics network, will facilitate my ongoing leadership in this critical discipline as well as enhancing the international standing of biostatistics in Australia.
Implementing Multiple Imputation With Sensitivity Analysis In Large-scale Longitudinal Studies
Funder
National Health and Medical Research Council
Funding Amount
$473,507.00
Summary
Missing data arise in most research studies and if not handled appropriately can mean the study results are not correct. With researchers now conducting larger and longer studies the challenges posed by missing data are increasing. In this grant we study a powerful technique for handling missing data, which in its current form often cannot be applied effectively in large studies. By developing this approach we will improve the accuracy of results from large-scale epidemiological studies.
Methodological Research In Meta-analysis And Evidence Synthesis: An Evidence-based Methods Approach
Funder
National Health and Medical Research Council
Funding Amount
$431,000.00
Summary
Systematic reviews synthesize available research to determine whether policy, health service delivery, public health, and clinical interventions are effective. Statistical methods underpin the validity of the findings in systematic reviews. This research will evaluate and develop statistical methods for systematic reviews with the aim of improving the quality of reviews and ensuring healthcare decisions are based on reliable research syntheses.
Understanding The Disruption-driven Clinical Environment To Enable Improvement In Patient Safety
Funder
National Health and Medical Research Council
Funding Amount
$77,150.00
Summary
Medical staff work in busy, often disruptive environments. There is growing evidence that disruptions compromise patient safety, although this process is not well understood. This project aims to use novel statistical methods to elucidate the complex relationship between disruption and adverse patient outcomes. It will enable informed intervention design and provide the tools to accurately assess the impact of such interventions.