The Australia Medical Bioinformatics Resource (AMBeR)
Funder
National Health and Medical Research Council
Funding Amount
$2,185,000.00
Summary
This proposal is to build a new national medical bioinformatics resource - the Australian Medical Bioinformatics Resource (AMBeR) - and to enhance the national capacity in this important area. We aim to bring together Australia's unique resources for genetic epidemiology and genomics with high level expertise in bioinformatics and statistical science, conduct advanced methodological research, develop new research capacity and competitiveness in cutting-edge techniques, bring them to bear on impo ....This proposal is to build a new national medical bioinformatics resource - the Australian Medical Bioinformatics Resource (AMBeR) - and to enhance the national capacity in this important area. We aim to bring together Australia's unique resources for genetic epidemiology and genomics with high level expertise in bioinformatics and statistical science, conduct advanced methodological research, develop new research capacity and competitiveness in cutting-edge techniques, bring them to bear on important medical research problems, train young Australians in bioinformatics and advanced biostatistics, and transfer this expertise to the medical research community.Read moreRead less
Modelling Dynamic Correlations in the Volatility of Patents and Technical Change. National/community benefits include a clearer understanding of the relation between patents and industrial innovation, measuring the effects of patents on technical change, economic growth and job creation, and analysing their fluctuations over time. The project analyses the variability in technological innovations, measures the impact of innovations on total output and key factors of production, namely labour, cap ....Modelling Dynamic Correlations in the Volatility of Patents and Technical Change. National/community benefits include a clearer understanding of the relation between patents and industrial innovation, measuring the effects of patents on technical change, economic growth and job creation, and analysing their fluctuations over time. The project analyses the variability in technological innovations, measures the impact of innovations on total output and key factors of production, namely labour, capital, energy and materials, and emphasizes the usefulness of the results. Expected outcomes include changing current ideas regarding output generation, understanding broad issues underlying patents and their variability, advancing multi-disciplinary knowledge, using information intelligently and promoting a culture of innovation.Read moreRead less
Latent variable modelling of discrete choice experiments. Discrete choice experiments and models are used to forecast consumer responses to changes in products policies and programs worldwide. Recent research suggests key model assumptions are violated because error variances covary with observed and unobserved factors. In order to address this, we will model systematic relationships between error variances and observed (eg, prices, survey length) and unobserved (eg, 'convenience', 'reputation') ....Latent variable modelling of discrete choice experiments. Discrete choice experiments and models are used to forecast consumer responses to changes in products policies and programs worldwide. Recent research suggests key model assumptions are violated because error variances covary with observed and unobserved factors. In order to address this, we will model systematic relationships between error variances and observed (eg, prices, survey length) and unobserved (eg, 'convenience', 'reputation') factors to improve model reliability and accuracy. This should lead to more accurate models/forecasts, benefitting business and government, which addresses the national priority of 'frontier technologies, promoting an innovative culture and economy'.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240101190
Funder
Australian Research Council
Funding Amount
$451,000.00
Summary
Innovating and Validating Scalable Monte Carlo Methods. This project aims to develop innovative scalable Monte Carlo methods for statistical analysis in the presence of big data or complex mathematical models. Existing approaches to scalable Monte Carlo are only approximate, and their inaccuracies are difficult to quantify. This can have a detrimental impact on data-based decision making. The expected outcomes of this project are scalable Monte Carlo methods that are more accurate, fast and capa ....Innovating and Validating Scalable Monte Carlo Methods. This project aims to develop innovative scalable Monte Carlo methods for statistical analysis in the presence of big data or complex mathematical models. Existing approaches to scalable Monte Carlo are only approximate, and their inaccuracies are difficult to quantify. This can have a detrimental impact on data-based decision making. The expected outcomes of this project are scalable Monte Carlo methods that are more accurate, fast and capable of quantifying inaccuracies. Scientists and decision-makers will benefit from the ability to obtain timely, reliable insights for challenging applications.Read moreRead less
Modelling the Choices of Individuals. Individuals make decisions daily and some of these decisions have wide-reaching and long-term consequences, such as choices among housing, public transport, electoral candidates and health care options. The principal aim of this project is to develop reliable and valid ways to model individual level choice processes. Once completed, this will provide insights into ways to aggregate sampled observations when population-level applications are required, and all ....Modelling the Choices of Individuals. Individuals make decisions daily and some of these decisions have wide-reaching and long-term consequences, such as choices among housing, public transport, electoral candidates and health care options. The principal aim of this project is to develop reliable and valid ways to model individual level choice processes. Once completed, this will provide insights into ways to aggregate sampled observations when population-level applications are required, and allow us to compare and test several competing theories of choice behaviour. This will enable us to make contributions to understanding and modelling human decision making in many fields ranging from marketing to medicine.Read moreRead less
Econometric Models for Marketing Decision Making. This project aims to develop methods to more efficiently allocate marketing resources across a range of media, including new media, such as the internet and social media, and compare them with with traditional media such as television and newspapers. To achieve this, the project will develop new methods and econometric models that employ data that capture both exposure to advertising media and downstream purchases at the individual-level. The exp ....Econometric Models for Marketing Decision Making. This project aims to develop methods to more efficiently allocate marketing resources across a range of media, including new media, such as the internet and social media, and compare them with with traditional media such as television and newspapers. To achieve this, the project will develop new methods and econometric models that employ data that capture both exposure to advertising media and downstream purchases at the individual-level. The expected outcome is that Australian companies will make more efficient use of their marketing budget, and better assess how to integrate new and old media into multimedia marketing communication campaigns.Read moreRead less
Innovative Use of Customer Data for Business Growth. This project aims to apply and adapt the latest machine learning techniques to enable companies to utilise their existing customer data to reveal purchase motivations, product preferences, and responsiveness to marketing communications for each single customer. A widespread practice in marketing is to partition customers into broad groups, but customers expect products and services that are tailored to their individual needs. This presents ex ....Innovative Use of Customer Data for Business Growth. This project aims to apply and adapt the latest machine learning techniques to enable companies to utilise their existing customer data to reveal purchase motivations, product preferences, and responsiveness to marketing communications for each single customer. A widespread practice in marketing is to partition customers into broad groups, but customers expect products and services that are tailored to their individual needs. This presents extreme challenges due to the size and complexity of customer databases. The expected outcomes will enable Australian companies to attract and retain more customers, and make more efficient use of their marketing budget. Benefits include equipping companies to better compete domestically and globally.Read moreRead less