Discovery Early Career Researcher Award - Grant ID: DE160100741
Funder
Australian Research Council
Funding Amount
$382,274.00
Summary
Tractable Bayesian algorithms for intractable Bayesian problems. This project seeks to develop computationally efficient and scalable Bayesian algorithms to estimate the parameters of complex models and ensure inferences drawn from the models can be trusted. Bayesian parameter estimation and model validation procedures are currently computationally intractable for many complex models of interest in science and technology. These include biological processes such as the efficacy of heart disease, ....Tractable Bayesian algorithms for intractable Bayesian problems. This project seeks to develop computationally efficient and scalable Bayesian algorithms to estimate the parameters of complex models and ensure inferences drawn from the models can be trusted. Bayesian parameter estimation and model validation procedures are currently computationally intractable for many complex models of interest in science and technology. These include biological processes such as the efficacy of heart disease, wound healing and skin cancer treatments. Potential outcomes of the project include new algorithms to significantly economise computations and improved understanding of the mechanisms of experimental data generation. Improved models of wound healing, skin cancer growth and heart physiology supported by these algorithms could improve population health.Read moreRead less
Development and validation of virtual epithelial cancer models using an integrated modelling and experimental three-dimensional approach. The mathematical and experimental modelling of the human prostate and ovary applying quantitative bioengineering concepts will lead to virtual cancer models. This project aims to validate these multi-scale models to delineate biological and pathological avenues in healthy and disease tissue and improve prevention and treatment of prostate and ovarian cancer.
Development and validation of virtual epithelial cancer models using an integrated modelling and experimental three-dimensional approach. The mathematical and experimental modelling of the human prostate and ovary applying quantitative bioengineering concepts will lead to virtual cancer models. This project aims to validate these multi-scale models to delineate biological and pathological avenues in healthy and disease tissue and improve prevention and treatment of prostate and ovarian cancer.
Discovery Early Career Researcher Award - Grant ID: DE120101113
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Mathematical modelling of breast cancer immunity: guiding the development of preventative breast cancer vaccines. The project will apply various methods from mathematical modelling to simulate anti-breast cancer immune responses to incipient tumours. Results from simulation and analysis will help develop, assess, and optimise preventative breast cancer vaccines for further testing in future experimental studies.
Discovery Early Career Researcher Award - Grant ID: DE150101842
Funder
Australian Research Council
Funding Amount
$345,000.00
Summary
New mathematical models for capturing heterogeneity of human brain tissue. This project aims to understand the impact of the heterogeneity of brain tissue on Magnetic Resonance Imaging (MRI) data in both healthy and diseased human brains, and to extract and quantify information on heterogeneity from the data. The project aims to develop novel mathematical and computational approaches to model the heterogeneity of the human brain. The project aims to identify new biomarkers for classifying differ ....New mathematical models for capturing heterogeneity of human brain tissue. This project aims to understand the impact of the heterogeneity of brain tissue on Magnetic Resonance Imaging (MRI) data in both healthy and diseased human brains, and to extract and quantify information on heterogeneity from the data. The project aims to develop novel mathematical and computational approaches to model the heterogeneity of the human brain. The project aims to identify new biomarkers for classifying different brain diseases, based on the extent of heterogeneity across different brain tissue. Results will be validated against extensive MRI scanning data of patients. This project aims to advance state-of-the-art techniques in human brain MRI data analysis.Read moreRead less
How microbes build their environments through evolutionary feedback. The fitness landscape, a key evolutionary concept, relates genes or traits to reproductive fitness. However, this has been challenged by organisms that distort the landscape by changing their environments. This project aims to develop a new mathematical model that restores the landscape concept by extending it to accommodate niche construction. This framework will be applied to microorganisms that alter their environments, for ....How microbes build their environments through evolutionary feedback. The fitness landscape, a key evolutionary concept, relates genes or traits to reproductive fitness. However, this has been challenged by organisms that distort the landscape by changing their environments. This project aims to develop a new mathematical model that restores the landscape concept by extending it to accommodate niche construction. This framework will be applied to microorganisms that alter their environments, for example, by provoking and subverting the host immune system, and by inducing behavioural change in hosts. These processes alter how natural selection operates on microbes and thus lead to important evolutionary feedback. The model will be used to examine antibiotic resistance, pathogen virulence and how microbiomes develop.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100944
Funder
Australian Research Council
Funding Amount
$427,068.00
Summary
Statistical frameworks for high-parameter imaging cytometry data. The project aims to develop statistical and bioinformatics methodology for characterising the complex interactions between cells in their native environment. Recent advances in imaging cytometry technologies have made it possible to observe the behaviour of multiple cell-types in tissue concurrently. The intended outcome is a suite of statistical methodologies that are crucial for addressing a variety of biological problems with t ....Statistical frameworks for high-parameter imaging cytometry data. The project aims to develop statistical and bioinformatics methodology for characterising the complex interactions between cells in their native environment. Recent advances in imaging cytometry technologies have made it possible to observe the behaviour of multiple cell-types in tissue concurrently. The intended outcome is a suite of statistical methodologies that are crucial for addressing a variety of biological problems with these state-of-the-art technologies. This work will advance knowledge in bioinformatics, statistics and image analysis, providing benefits to scientists studying the fundamental behaviour of cells and underlying disease mechanisms.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190100805
Funder
Australian Research Council
Funding Amount
$382,656.00
Summary
Phylogenetic methods for genome surveillance of microbial pathogens. This project aims to develop phylogenetic approaches to harness the potential evolution of bacterial and virus pathogens data and to improve early detection of infectious outbreaks. Genome surveillance programs consist in routine sequencing of particular organisms to track their evolution over time. Such programs currently exist for important bacterial and virus pathogens. This project expects to develop computational methods t ....Phylogenetic methods for genome surveillance of microbial pathogens. This project aims to develop phylogenetic approaches to harness the potential evolution of bacterial and virus pathogens data and to improve early detection of infectious outbreaks. Genome surveillance programs consist in routine sequencing of particular organisms to track their evolution over time. Such programs currently exist for important bacterial and virus pathogens. This project expects to develop computational methods to improve our understanding of pathogen outbreak emergence and infectious spread using genome data. This project will expand our knowledge base and research capability in the evolution and epidemiology of infectious agents, and aid in the prevention and control strategies of infectious disease benefiting the research priorities of food and health.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100284
Funder
Australian Research Council
Funding Amount
$444,000.00
Summary
Multiscale mathematical modelling to gain insights into hepatitis viruses. This project aims to use mathematical modelling to study hepatitis viruses at multiple levels. The project expects to develop complex yet analysable mathematical models to comprehend the fundamental biology of hepatitis viruses by elucidating longitudinal patterns in viral and immune markers at intracellular and cellular levels, and advance a new subfield in mathematical biology, i.e., modelling codependent human viruses. ....Multiscale mathematical modelling to gain insights into hepatitis viruses. This project aims to use mathematical modelling to study hepatitis viruses at multiple levels. The project expects to develop complex yet analysable mathematical models to comprehend the fundamental biology of hepatitis viruses by elucidating longitudinal patterns in viral and immune markers at intracellular and cellular levels, and advance a new subfield in mathematical biology, i.e., modelling codependent human viruses. Expected outcomes of the project include new generalized mathematical tools, biological insights that may aid research beyond the scope of this project, and strong interdisciplinary collaborations. Expected benefits include an increased capacity of the research community in Australia to use mathematical models in virology.Read moreRead less
Uncovering novel metabolic processes in eukaryotic cells. This project aims to investigate the origin and function of the large number of chemically undefined metabolites that occur in all cells. The project will utilise advanced analytical techniques, as well as computational and genetic approaches, to characterise the chemical structures of these metabolites and identity the enzymes involved in their synthesis and degradation. It will provide new information on the metabolic capacity of eukary ....Uncovering novel metabolic processes in eukaryotic cells. This project aims to investigate the origin and function of the large number of chemically undefined metabolites that occur in all cells. The project will utilise advanced analytical techniques, as well as computational and genetic approaches, to characterise the chemical structures of these metabolites and identity the enzymes involved in their synthesis and degradation. It will provide new information on the metabolic capacity of eukaryotic cells and allow the generation of more accurate models of metabolism. These outcomes have important biotechnology applications and will identify metabolic processes that underpin normal and disease states in animals and human cells.Read moreRead less