Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statis ....Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statistical methods provide the opportunity to close this gap. The outcome will be identification of many genomic variants causing variation in complex traits. This will benefit scientific understanding of complex traits and the ability to predict traits for individuals from their genome sequence.Read moreRead less
Relative free energies from nonequilibrium simulations: algorithms for determination of binding affinities, conformational states and phase transitions. Leading edge research will enable state of the art techniques in statistical mechanics to be applied to practical problems. All processes in biological, chemical and physical systems are governed by their free energy landscape, often only accessible computationally. This project will lead to an advanced tool for free energy calculation. Advanc ....Relative free energies from nonequilibrium simulations: algorithms for determination of binding affinities, conformational states and phase transitions. Leading edge research will enable state of the art techniques in statistical mechanics to be applied to practical problems. All processes in biological, chemical and physical systems are governed by their free energy landscape, often only accessible computationally. This project will lead to an advanced tool for free energy calculation. Advancement of emerging technologies in nanoscience, porous materials, membrane transport and drug design will benefit from this capability. The project therefore addresses the Priority Goal 'Breakthrough science'. A PhD student and an Early Career Research will be trained in research, gaining a range of valuable skills in theory and simulation. Read moreRead less
Dissipation and relaxation in statistical mechanics. This project studies the mathematical conditions for relaxation either to equilibrium or to steady states, which is important in predicting behaviour in diverse fields including climate modelling, materials science, nanotechnology and biology. Early career researchers will be involved in the project, gaining valuable skills in theory and simulation.
Improving likelihood estimators: theory and applications to analysing productivity and efficiency and forecasting of probability of economic recession. This project aims to improve one of the most popular statistical methods to empower applied researchers with a more reliable analytical tool. This project will develop mathematical theory and use it to analyse patterns of economic growth, productivity and efficiency of countries. This can be used to forecast probability of entering economic reces ....Improving likelihood estimators: theory and applications to analysing productivity and efficiency and forecasting of probability of economic recession. This project aims to improve one of the most popular statistical methods to empower applied researchers with a more reliable analytical tool. This project will develop mathematical theory and use it to analyse patterns of economic growth, productivity and efficiency of countries. This can be used to forecast probability of entering economic recession, with a focus on Australia.Read moreRead less
Properties of nonequilibrium steady states. A nonequilibrium steady state (NESS) occurs when work is performed on a system and the heat so generated is absorbed by a thermostatting mechanism. The system settles into steady state and its properties no longer change. Almost all experimental systems of interest are in a nonequilibrium state, so understanding NESSs is highly significant. Unlike time stationary equilibrium states, the distribution of microstates in a NESS cannot be described by simpl ....Properties of nonequilibrium steady states. A nonequilibrium steady state (NESS) occurs when work is performed on a system and the heat so generated is absorbed by a thermostatting mechanism. The system settles into steady state and its properties no longer change. Almost all experimental systems of interest are in a nonequilibrium state, so understanding NESSs is highly significant. Unlike time stationary equilibrium states, the distribution of microstates in a NESS cannot be described by simple closed form distributions. This project will determine properties, symmetries and extrema of NESS using concepts and theorems developed for studying transient nonequilibrium states, and will also determine if approximate, physically relevant forms of the phase space distributions can be developed.Read moreRead less
The improvement of climate change investigations by developing and applying innovative evolutionary subset time series modelling using semi-parametric sparse-patterned approaches. With an estimated US$6.98 trillion loss indicated in the Stern review, severe climate change will make world climate conditions harsher and more likely include large natural climate disasters. The health of the Australian economy is critically dependent on decisions of environmental managers. However, most problems of ....The improvement of climate change investigations by developing and applying innovative evolutionary subset time series modelling using semi-parametric sparse-patterned approaches. With an estimated US$6.98 trillion loss indicated in the Stern review, severe climate change will make world climate conditions harsher and more likely include large natural climate disasters. The health of the Australian economy is critically dependent on decisions of environmental managers. However, most problems of complexity arising in climate change involve issues on which we do not possess a deep understanding. This project draws upon a set of inter-disciplinary concepts and models centred in neural networks that enable us to advance our understanding of complexity, leading to superior quantitative tools and models to allow for improved environmental decision-making.
Read moreRead less
A Genomic Dissection of Natural Adaptation in Mate Recognition. Adaptation is a fundamental area of evolutionary biology but we know surprisingly little about its underlying genetic basis. As a process, adaptation poses several challenges for Australian society including bacterial evolution of resistance to antibiotics, HIV resistance to antiviral medications and the evolution of pesticide resistance in agricultural pests. This study will use a model system and genomic tools to test theoretical ....A Genomic Dissection of Natural Adaptation in Mate Recognition. Adaptation is a fundamental area of evolutionary biology but we know surprisingly little about its underlying genetic basis. As a process, adaptation poses several challenges for Australian society including bacterial evolution of resistance to antibiotics, HIV resistance to antiviral medications and the evolution of pesticide resistance in agricultural pests. This study will use a model system and genomic tools to test theoretical models of the genetic basis of adaptation. This integrative approach will enhance Australia's research profile in genomics and evolutionary biology. The project will provide emerging scientists with skills in areas including genomics, molecular biology, evolutionary biology and agricultural genetics.Read moreRead less
Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis. The genomics revolution has made it possible to measure thousands of DNA variants in individuals. This information can be used in many ways, including to find genes that cause variation between individuals in a population and to estimate the size of the population in the past. Our study will lead an analysis method that will extract more information out of such data. This will improve the effi ....Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis. The genomics revolution has made it possible to measure thousands of DNA variants in individuals. This information can be used in many ways, including to find genes that cause variation between individuals in a population and to estimate the size of the population in the past. Our study will lead an analysis method that will extract more information out of such data. This will improve the efficiency of gene mapping methods, including applications in humans for traits related to productive ageing and a healthy start to life, will allow the estimation of genetic relatedness and genetic variation in natural populations, and will lead to more efficient selection programs in agricultural populations.Read moreRead less
Advances in Sequential Monte Carlo Methods for Complex Bayesian Models. This project aims to develop efficient statistical algorithms for parameter estimation of complex stochastic models that currently cannot be handled. Parameter estimation is an essential component of mathematical modelling for answering scientific questions and revealing new insights. Current parameter estimation methods can be inefficient and require too much user intervention. This project will develop novel Bayesian alg ....Advances in Sequential Monte Carlo Methods for Complex Bayesian Models. This project aims to develop efficient statistical algorithms for parameter estimation of complex stochastic models that currently cannot be handled. Parameter estimation is an essential component of mathematical modelling for answering scientific questions and revealing new insights. Current parameter estimation methods can be inefficient and require too much user intervention. This project will develop novel Bayesian algorithms that are optimally automated and efficient by exploiting ever-improving parallel computing devices. The new methods will allow practitioners to process realistic models, enabling new scientific discoveries in a wide range of disciplines such as biology, ecology, agriculture, hydrology and finance.Read moreRead less
New Bayesian methodology for understanding complex systems using hidden Markov models and expert opinion, environmental, robotics and genomics applications. This project aims to merge four areas of intense international interest in describing complex systems: hidden Markov models and mixtures, semi-parametric and nonparametric approaches, true combination of expert opinion with data, and new Bayesian computational methods based on perfect sampling and particle sampling. The project will signific ....New Bayesian methodology for understanding complex systems using hidden Markov models and expert opinion, environmental, robotics and genomics applications. This project aims to merge four areas of intense international interest in describing complex systems: hidden Markov models and mixtures, semi-parametric and nonparametric approaches, true combination of expert opinion with data, and new Bayesian computational methods based on perfect sampling and particle sampling. The project will significantly contribute to statistical methodology and its ability to inform about real-world problems. A strong focus on applications to genomics, robotics and environmental modelling will bring immediate research and monetary benefit for industry. Expected outcomes include enhanced cross-disciplinary and international linkages, publications, industry-funded projects and highly trained graduates.Read moreRead less