Large-Scale Multi-Omic Analysis And Risk Prediction Of Complex Human Disease
Funder
National Health and Medical Research Council
Funding Amount
$321,414.00
Summary
A major aim of medicine is to prevent disease, which is often more successful and cost-effective than treating an already existing condition. Common diseases, such as autoimmune and cardiovascular diseases, have a predisposing genetic basis. We will conduct genetic analysis of large datasets of coeliac disease and cardiovascular disease to better identify individuals at increased risk and to better understand the underlying biological processes through which genetics act to affect one's risk.
A study of the archaeology of Caucasian Iberia with implications for grazing management in Australia. This multi-disciplinary project will promote a younger generation of talented postgraduate and undergraduate students in a wide variety of fields, including archaeology, geomatic engineering, conservation of material culture, environmental and other natural sciences. The highlands of the Caucasus, located in a bioclimatic zone with a long history of alpine grazing, can also provide answers to qu ....A study of the archaeology of Caucasian Iberia with implications for grazing management in Australia. This multi-disciplinary project will promote a younger generation of talented postgraduate and undergraduate students in a wide variety of fields, including archaeology, geomatic engineering, conservation of material culture, environmental and other natural sciences. The highlands of the Caucasus, located in a bioclimatic zone with a long history of alpine grazing, can also provide answers to questions such as the effect of grazing on biodiversity and the rehabilitation of fragile ecosystems, which may inform management and conservation activities in analogous highland country in Australia. The project will also ensure that exhibitions illustrating the rich heritage of Caucasus will reach Australian shores.Read moreRead less
Propagating Neural Waves: Combined Experimental and Modelling Study. The project is designed to measure propagating neural waves in visual areas of the brain to discover why and how they are created, how they interact with sensory inputs, and whether they can support brain plasticity and learning. Recent analysis of the brain’s electrical signals has showed that nerve cell activity is often organised into propagating waves, but how these waves are created, and what role they play in brain inform ....Propagating Neural Waves: Combined Experimental and Modelling Study. The project is designed to measure propagating neural waves in visual areas of the brain to discover why and how they are created, how they interact with sensory inputs, and whether they can support brain plasticity and learning. Recent analysis of the brain’s electrical signals has showed that nerve cell activity is often organised into propagating waves, but how these waves are created, and what role they play in brain information processing, remains unknown. The project plans to develop new methods for processing large-scale neural data, and to apply these methods to learn about propagating neural waves. These results may improve our understanding of how neural circuits function, eventually leading to clinical and technological advances.Read moreRead less
Complex dynamical systems: inferring form and function of interacting biological systems. Often in biology a large number of simple parts interacting according to simple rules can result in behaviour that is rich and varied. This project aims to develop the mathematics of complex systems theory to describe how such collections of simple interacting parts can form large complicated structures, and to deduce what dynamical behaviour can result.
Discovery Early Career Researcher Award - Grant ID: DE140100620
Funder
Australian Research Council
Funding Amount
$395,220.00
Summary
Inference, control and protection of interdependent spatial networked structures. Networked structures are everywhere and modern societies largely depend on their proper functioning. Some of these networks are spatial with each node having a geographical tag. Examples include power grids, the internet and transportation networks. These networks are often interdependent where their functioning depends on each other. This project will establish a mathematical framework to efficiently observe and c ....Inference, control and protection of interdependent spatial networked structures. Networked structures are everywhere and modern societies largely depend on their proper functioning. Some of these networks are spatial with each node having a geographical tag. Examples include power grids, the internet and transportation networks. These networks are often interdependent where their functioning depends on each other. This project will establish a mathematical framework to efficiently observe and control interdependent spatial networks and develop design strategies in order to maximise residency of spatial networks against catastrophic failures in their components. The outcomes of the project will protect the Australian power grid and transportation networks against random and intentional failures. Read moreRead less
Mapping EQTL To Dissect The Genetic Basis Of Complex Trait Variation
Funder
National Health and Medical Research Council
Funding Amount
$719,525.00
Summary
People vary in traits such as height and blood pressure and in their susceptibility to common disease. Part of these differences between individuals is because of their genetic make-up. This research is about understanding which of the genes are involved in common variation and how they work. In particular, the researchers investigate if variation in DNA sequence causes genes to be expressed more or less and how gene expression affects risk of disease.
Developing And Applying Biologically Plausible Statistical Models For Normal And Non-normal Family Data
Funder
National Health and Medical Research Council
Funding Amount
$339,700.00
Summary
Although molecular and computing advances have enabled more detailed investigations of inherited diseases and the ability to fit realistic statistical models to these data, limitations still exist when analysing family data. Often only basic statistical analyses are performed, due to the lack of understanding of complexities within the data and-or inability of researchers to fit appropriate statistical models. These factors have hampered the search for genes and environmental factors influencing ....Although molecular and computing advances have enabled more detailed investigations of inherited diseases and the ability to fit realistic statistical models to these data, limitations still exist when analysing family data. Often only basic statistical analyses are performed, due to the lack of understanding of complexities within the data and-or inability of researchers to fit appropriate statistical models. These factors have hampered the search for genes and environmental factors influencing common diseases. This project aims to develop novel, biologically realistic statistical models for investigation of common, complex diseases, such as heart disease and cancer, in families. These models will incorporate both measured and unmeasured genetic and environmental factors, and will be applicable to both normally distributed and non-normally distributed traits. Model fitting will use computer-intensive simulation techniques. Application of the models to data from two large pre-existing studies of international renown, the Victorian Family Heart Study and the Australian Prostate Cancer Family Study, will enable a better understanding of the genetic and environmental factors influencing heart disease and cancer. The models will also be applicable to many other studies of diseases which use data from families, and allow more accurate and useful information to be obtained from data. Software will also be made freely available to other researchers. This will ultimately translate into better outcomes from familial genetic research, and eventually, better prevention, detection, and treatment of the diseases.Read moreRead less