Prof Speed is a statistician specializing in bioinformatics and computational biology, applying my skills in support of basic research in molecular and cell biology and genetics.
I am a statistician specializing in bioinformatics and computational biology, applying my skills in support of basic research in molecular and cell biology and genetics.
Development And Evaluation Of Statistical Methods And Software For Analysis Of Complex Genetic Disease Data
Funder
National Health and Medical Research Council
Funding Amount
$1,250,371.00
Summary
What are the major factors underpinning complex genetic diseases like diabetes, bipolar disorder or cancer? To answer this question new tools are needed, including software for mining the human genome with interactions between the genome and environment being incorporated. This is our focus. It will form the basis of a superior understanding of the overall process leading to disease and hence better predictions with important ramifications for new treatments and health care planning.
Novel Statistical Methods For The Analysis Of Meausred Genetic And Environmental Risk Factors In Twin Studies
Funder
National Health and Medical Research Council
Funding Amount
$478,314.00
Summary
Studies on twins are an important way to determine whether the risk of disease is likely to be influenced by genetic factors but have traditionally focussed on unmeasured factors. New epidemiological studies measure thousands of genetic variants on many participants. This project will extend methods for analysing data within and between twin pairs to determine whether risk factors are likely to be causal and therefore should be the subject of further designed studies based on intervention.
Novel Statistical Methods For Genetic Epidemiology
Funder
National Health and Medical Research Council
Funding Amount
$481,505.00
Summary
We are in the midst of a genomics revolution that is transforming epidemiology, medicine and drug discovery. However, the scarcity of sophisticated statistical techniques to deal with the complicated problems inherent in genetic investigations of complex diseases is currently the critical factor limiting the success of human gene discovery programs. Statistical genetic methodology is currently one of the fastest developing areas of epidemiology. In information-intensive' areas such as genetic ep ....We are in the midst of a genomics revolution that is transforming epidemiology, medicine and drug discovery. However, the scarcity of sophisticated statistical techniques to deal with the complicated problems inherent in genetic investigations of complex diseases is currently the critical factor limiting the success of human gene discovery programs. Statistical genetic methodology is currently one of the fastest developing areas of epidemiology. In information-intensive' areas such as genetic epidemiology, genomics, and proteomics, there is a high demand for data analysis and statistical skills. WA has some world class expertise in statistical science, both in academia and in industry. However, this expertise has not yet been applied in a system way to genetic data analysis. We propose to undertake advanced methodological research in statistical genetics and bioinformatics, to produce easy-to-use and accessible software tools and resources that allow methodological advances to be accessed by the Australian research community, and to apply our new methods and tools both to specific disease research and to the developing human genome epidemiology (HuGE) enterprise in WA. These new initiatives in methodological research will draw together a number of currently separate research strands and will provide new tools and resources that will allow applied Australian programs to improve the efficiency of their research into the causes of important. Methodological development in both bioinformatics and statistical genetics are recognized international areas of need.Read moreRead less
Statistical Analyses Of Breast Cancer Risks For Australian BRCA1 And BRCA2 Mutation Carriers
Funder
National Health and Medical Research Council
Funding Amount
$424,628.00
Summary
About 10 years ago two genes, called BRCA1 and BRCA2, were discovered. The normal function of these genes is to prevent breast and other cancers from developing. All people have two copies of each gene, one inherited from their mother and one from their father. Women who have inherited a fault in one copy are at increased risk of breast and ovarian cancer. There has been considerable controversy about what their actual cancer risks are, especially about how those risks might depend on their age. ....About 10 years ago two genes, called BRCA1 and BRCA2, were discovered. The normal function of these genes is to prevent breast and other cancers from developing. All people have two copies of each gene, one inherited from their mother and one from their father. Women who have inherited a fault in one copy are at increased risk of breast and ovarian cancer. There has been considerable controversy about what their actual cancer risks are, especially about how those risks might depend on their age. We have already conducted studies on this and have developed the necessary statistical methods to address these issues by analysing data from the families in which there are faulty genes. In this study we propose to use two large Australian studies, one of families with multiple-cases of breast cancer (Kathleen Cuningham Consortium for Research on Familial Breast Cancer; kConFab) and the other of the families of women with breast cancer chosen, irrespective of their family cancer histories, through the Victorian and NSW Cancer Registries (Australian Breast Cancer Family Study; ABCFS). A large amount of work has already been conducted to identify these families and test them for faults in BRCA1 and BRCA2. There are over 350 families who carry faults, making this one of the largest studies of its type in the world. We will check the cancer histories of these families and determine which members have, or are likely to have, inherited a faulty gene. We will then estimate the breast and ovarian cancer risks accurately, and with much more precision, than has been done previously. We will also use these large datasets to develop a simple method to identify which Australian women are most likely to carry a fault in BRCA1 or BRCA2, based on their personal and family cancer histories. This study will assist genetic counsellors inform Australian women who consider mutation testing for BRCA1 and BRCA2 about their cancer risks, and help make breast cancer genetics more cost effective.Read moreRead less
Bayesian estimation of flexible spatial models with applications in medical imaging and econometric modeling. This project aims to develop statistical methodology for estimating flexible highly parameterised Bayesian spatial models. The flexible models examined will include regression, choice and time series models for data that is spatially registered. Spatial smoothing of parameters in the models will involve application of hierarchical spatial prior distributions. The resulting methodology wi ....Bayesian estimation of flexible spatial models with applications in medical imaging and econometric modeling. This project aims to develop statistical methodology for estimating flexible highly parameterised Bayesian spatial models. The flexible models examined will include regression, choice and time series models for data that is spatially registered. Spatial smoothing of parameters in the models will involve application of hierarchical spatial prior distributions. The resulting methodology will be applied to the analysis of medical imaging data and to the estimation of spatial econometric models of residential real estate prices. The expected outcomes include developments in the frontier framework of Bayesian computational estimation methodology, improved methods for medical image processing and estimation of high resolution spatial models of residential real estate prices in Australian metropolitan centres.Read moreRead less
Complex data, model selection and bootstrap inference. The project will provide new statistical methods and associated software for the analysis and modelling of complex data, as well as quality research training. This project will benefit researchers in statistics and users of statistics who encounter the complex data considered in this project and who need to model and make inferences from these data. Since these kinds of data arise in many areas (such as medicine, genetics, chemistry etc), ....Complex data, model selection and bootstrap inference. The project will provide new statistical methods and associated software for the analysis and modelling of complex data, as well as quality research training. This project will benefit researchers in statistics and users of statistics who encounter the complex data considered in this project and who need to model and make inferences from these data. Since these kinds of data arise in many areas (such as medicine, genetics, chemistry etc), Australia and Australian industry will ultimately benefit from the proposed research. The strengthening of international link and the training of highly trained research scientists in an area of national importance will also benefit Australia.Read moreRead less
Innovations in Bayesian likelihood-free inference. Bayesian inference is a statistical method of choice in applied science. This project will develop innovative tools which permit Bayesian inference in problems considered intractable only a few years ago. These methods will expedite advances in multidisciplinary research across a range of applications. With these foundations, this project will accelerate national research efforts into improving frameworks for projecting trends in water availabil ....Innovations in Bayesian likelihood-free inference. Bayesian inference is a statistical method of choice in applied science. This project will develop innovative tools which permit Bayesian inference in problems considered intractable only a few years ago. These methods will expedite advances in multidisciplinary research across a range of applications. With these foundations, this project will accelerate national research efforts into improving frameworks for projecting trends in water availability and management, the impact of climate extremes, telecommunications engineering, HIV and infectious disease modelling and biostatistics. With many sectors unable to recruit appropriately trained statisticians within Australia, this project will train four PhD students in Bayesian statistics.
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