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
Prior sensitivity analysis for Bayesian Markov chain Monte Carlo output. This project aims to develop the first set of techniques to implement an automated output sensitivity analysis for Markov Chain Monte Carlo (MCMC) estimation methods. Computationally intense Bayesian MCMC provide a powerful alternative to classical methods for the estimation of economic models. An obstacle to their wider application is that researchers need to specify prior beliefs about model parameters that will affect t ....Prior sensitivity analysis for Bayesian Markov chain Monte Carlo output. This project aims to develop the first set of techniques to implement an automated output sensitivity analysis for Markov Chain Monte Carlo (MCMC) estimation methods. Computationally intense Bayesian MCMC provide a powerful alternative to classical methods for the estimation of economic models. An obstacle to their wider application is that researchers need to specify prior beliefs about model parameters that will affect the results. The expected outcomes will enable researchers to undertake a routine assessment of the sensitivity of the results to prior inputs.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
The genetics of four ancient 'Kings' of Sahul and Sunda. This project aims to recover all the genetic information from four ancient humans. Two of these iconic specimens come from Australia and two from Malaysia. We will sequence the entire DNA (genomes) and proteins (proteome) of Mungo Man (Willandra), the Yidinji King (Cairns), the Deep Skull (Borneo) and the Bewah specimen (Malaysian Peninsula). This will provide a better understanding of the settlement of Australia and new knowledge about th ....The genetics of four ancient 'Kings' of Sahul and Sunda. This project aims to recover all the genetic information from four ancient humans. Two of these iconic specimens come from Australia and two from Malaysia. We will sequence the entire DNA (genomes) and proteins (proteome) of Mungo Man (Willandra), the Yidinji King (Cairns), the Deep Skull (Borneo) and the Bewah specimen (Malaysian Peninsula). This will provide a better understanding of the settlement of Australia and new knowledge about the ancient people of Australasia and their relationship to other human populations worldwide. The research will use cutting-edge methods of DNA and protein sequencing of ancient human material and will provide critical reference genomes / proteomes that will anchor future research.Read moreRead less
Molecular design of complex lubricants to reduce friction. We will investigate the molecular level design of friction modifiers for a new generation of industrial lubricants. The goal is to dramatically reduce friction between moving mechanical parts, hence increasing energy efficiency in machines and reducing global greenhouse gas emissions. We will design and test these new friction modifiers by a combination of theoretical and computational methods based in statistical mechanics and nonequili ....Molecular design of complex lubricants to reduce friction. We will investigate the molecular level design of friction modifiers for a new generation of industrial lubricants. The goal is to dramatically reduce friction between moving mechanical parts, hence increasing energy efficiency in machines and reducing global greenhouse gas emissions. We will design and test these new friction modifiers by a combination of theoretical and computational methods based in statistical mechanics and nonequilibrium molecular dynamics and directly compare results with experimental measurements. Our investigations will pave the way to develop new cost-effective friction modifiers without the need for traditional and costly trial and error laboratory based experimentation.Read moreRead less
Genetic architecture and evolution of complex traits across populations. Most human traits have a genetic component and display substantial diversity within and among populations. How natural selection changes and maintains genetic variation in human traits is a long-standing question in evolution that the proposed project aims to answer. Using innovative statistical methods and largest genomic “big” datasets ever across populations of different ancestral backgrounds, this project expects to gen ....Genetic architecture and evolution of complex traits across populations. Most human traits have a genetic component and display substantial diversity within and among populations. How natural selection changes and maintains genetic variation in human traits is a long-standing question in evolution that the proposed project aims to answer. Using innovative statistical methods and largest genomic “big” datasets ever across populations of different ancestral backgrounds, this project expects to generate new knowledge on the roles of natural selection in shaping the genetic variation in traits and identify key factors that drive the differentiation of human populations. These outcomes will significantly improve our understanding on the evolution of human traits and adaptation of populations to changing environments.Read moreRead less
Robust methods for heteroscedastic regression models for time series. What is the variability of the exchange rate of the Euro to the Australian dollar? Can the use of the electrocardiogram of a patient be improved as a diagnostic tool for heart disease? A well-known limitation of the existing statistical methods for answering these types of questions is that a small proportion of extreme observations have the potential to lead to results that are more in agreement with the outliers than with bu ....Robust methods for heteroscedastic regression models for time series. What is the variability of the exchange rate of the Euro to the Australian dollar? Can the use of the electrocardiogram of a patient be improved as a diagnostic tool for heart disease? A well-known limitation of the existing statistical methods for answering these types of questions is that a small proportion of extreme observations have the potential to lead to results that are more in agreement with the outliers than with bulk of the data. As a consequence, the statistical analyses may lead to wrong conclusions. This project aims to develop new methodologies to solve this problem for a large class of studies. Applications to stock market risk, exchange rate, and diagnosis of heart diseases will illustrate the new methods.Read moreRead less
The origins of Australia's non-Pama-Nyungan speaking people. This project aims to test the likelihood of multiple migrations into Australia before European arrival and determine if the phylogenetic relationships among non-Pama-Nyungan languages is mirrored by their speakers’ genomic phylogenetic relationships. The non-Pama-Nyungan First People of Australia speak an extraordinary number and diversity of Aboriginal languages, but the origins of these languages and the genomic diversity of the peop ....The origins of Australia's non-Pama-Nyungan speaking people. This project aims to test the likelihood of multiple migrations into Australia before European arrival and determine if the phylogenetic relationships among non-Pama-Nyungan languages is mirrored by their speakers’ genomic phylogenetic relationships. The non-Pama-Nyungan First People of Australia speak an extraordinary number and diversity of Aboriginal languages, but the origins of these languages and the genomic diversity of the people who speak them are only now starting to be understood. There is a remarkable concordance between the Pama-Nyungan languages and the genomic diversity of their speakers. This research could show whether genomes change languages or vice versa, or whether they evolve together over time.Read moreRead less
The nature of standing genetic variation. This project aims to expand understanding of the genetic variation underlying phenotypic differences among individuals. The nature of genetic variation has broad consequences across biology, from the detection of causal genetic variants to the adaptation of natural populations. This project will take a novel experimental approach to test several long-standing assumptions about the effects of new mutations on individual traits and their joint pleiotropic ....The nature of standing genetic variation. This project aims to expand understanding of the genetic variation underlying phenotypic differences among individuals. The nature of genetic variation has broad consequences across biology, from the detection of causal genetic variants to the adaptation of natural populations. This project will take a novel experimental approach to test several long-standing assumptions about the effects of new mutations on individual traits and their joint pleiotropic effect on fitness. By expanding our understanding of how mutation, selection and drift interact, this project could provide significant improvements in our understanding of the genetic basis of phenotypes, and our ability to predict phenotypic evolution.Read moreRead less
Identification Power and Instrument Strength in Discrete Outcome Models. This project aims to develop new econometric and statistical techniques to quantify causal effects in treatment models with discrete outcomes. Expected outcomes include a much-needed weak instrument test, a measure for identification strength in partial identification setting, and an instrument-covariate selection procedure for high dimensional discrete models based identification power. The benefits include advanced knowle ....Identification Power and Instrument Strength in Discrete Outcome Models. This project aims to develop new econometric and statistical techniques to quantify causal effects in treatment models with discrete outcomes. Expected outcomes include a much-needed weak instrument test, a measure for identification strength in partial identification setting, and an instrument-covariate selection procedure for high dimensional discrete models based identification power. The benefits include advanced knowledge in econometrics and statistics, and enhanced tools for program evaluation and policy assessment in empirical causal analysis using observational data. The project falls into the category of smarter information use and is relevant to any national priority areas where policy interventions require assessment.Read moreRead less