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Discovery Early Career Researcher Award - Grant ID: DE200100988
Funder
Australian Research Council
Funding Amount
$425,333.00
Summary
From cells to whales: A mathematical framework to understand navigation. This project aims to understand what drives the navigation of small and large organisms. To achieve this, the project seeks to develop a mathematical framework that unifies models of navigation, communication and uncertainty, for the first time. This is significant as navigation underpins fundamental behaviour such as migration. Expected outcomes of this project include novel insights into the mechanisms underlying navigati ....From cells to whales: A mathematical framework to understand navigation. This project aims to understand what drives the navigation of small and large organisms. To achieve this, the project seeks to develop a mathematical framework that unifies models of navigation, communication and uncertainty, for the first time. This is significant as navigation underpins fundamental behaviour such as migration. Expected outcomes of this project include novel insights into the mechanisms underlying navigation, and new mathematical techniques required to construct the framework. The mathematical framework will be employed to explore and explain critical biological phenomena such as the impact of noise pollution on whale migration, and the conditions required for successful cellular navigation.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100200
Funder
Australian Research Council
Funding Amount
$418,398.00
Summary
Next generation causal inference methods for biological data. This project aims to develop next generation causal inference methods for analysing biological data especially the single cell sequencing data and their applications in cell biology. Although Artificial Intelligence and Statistical Machine Learning have been applied successfully in many fields, including biological research, there is still a serious lack of methods for interpreting and reasoning about the mechanism of biological syste ....Next generation causal inference methods for biological data. This project aims to develop next generation causal inference methods for analysing biological data especially the single cell sequencing data and their applications in cell biology. Although Artificial Intelligence and Statistical Machine Learning have been applied successfully in many fields, including biological research, there is still a serious lack of methods for interpreting and reasoning about the mechanism of biological systems, the ultimate goal of research in many areas. Efficient data-driven causality discovery approaches developed by the project will be a timely and significant contribution to the knowledge of biology and statistics as well as the battle against health threats.
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New mathematical approaches to learn the equations of life from noisy data. New mathematical models and mathematical modelling methods must be continually developed to interpret emerging biotechnology experiments. Contemporary research in tissue engineering involves growing tissues on 3d-printed scaffolds to mimic constrained in vivo geometries. Previous mathematical models of tissue growth focus on computationally expensive discrete mathematical models that are poorly suited for parameter infe ....New mathematical approaches to learn the equations of life from noisy data. New mathematical models and mathematical modelling methods must be continually developed to interpret emerging biotechnology experiments. Contemporary research in tissue engineering involves growing tissues on 3d-printed scaffolds to mimic constrained in vivo geometries. Previous mathematical models of tissue growth focus on computationally expensive discrete mathematical models that are poorly suited for parameter inference and experimental design. This project will deliver and deploy high-fidelity, computationally efficient moving boundary continuum mathematical models that will: (i) predict/interpret new experiments, (ii) provide quantitative insight into biological mechanisms, and (iii) enable reproducible experimental design.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100650
Funder
Australian Research Council
Funding Amount
$443,237.00
Summary
Behind the barrier: using mathematics to understand the neuro-immune system. This project aims to develop new mathematical methods to study healthy immune cell regulation in the brain and movement across the Blood Brain Barrier. The project expects to develop novel deterministic and stochastic mathematics that captures the stochasticity of immune cells in the Central Nervous System (brain and spine) and form the foundation of a new field of mathematical research: mathematical neuroimmunology. Ex ....Behind the barrier: using mathematics to understand the neuro-immune system. This project aims to develop new mathematical methods to study healthy immune cell regulation in the brain and movement across the Blood Brain Barrier. The project expects to develop novel deterministic and stochastic mathematics that captures the stochasticity of immune cells in the Central Nervous System (brain and spine) and form the foundation of a new field of mathematical research: mathematical neuroimmunology. Expected benefits of this project include new mathematical tools, biological insight, and strong interdisciplinary collaborations. From this project, Australia will be placed at the forefront of mathematical research in neuroimmunology, and there will be a complete understanding of homeostasis of the neuro-immune system. Read moreRead less
Mathematical models to connect experiments across biological scales. Understanding the function and development of organs is crucial to our understanding of fundamental biology. This project aims to address our inability to connect and understand behaviour between simple and complex biological experiments. This project expects to develop new mathematical theory and models to connect experiments across scales and complexity. Expected outcomes of this project include a new mathematical modelling f ....Mathematical models to connect experiments across biological scales. Understanding the function and development of organs is crucial to our understanding of fundamental biology. This project aims to address our inability to connect and understand behaviour between simple and complex biological experiments. This project expects to develop new mathematical theory and models to connect experiments across scales and complexity. Expected outcomes of this project include a new mathematical modelling framework, and advances in understanding in both biology and mathematics. This should provide significant benefits as using mathematical modelling to understand experimental connections will decrease the time- and financial- costs of performing experiments, while increasing efficiency and insight.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL220100005
Funder
Australian Research Council
Funding Amount
$3,350,000.00
Summary
CellMaps for cell fate decision making systems. The cell is the fundamental unit exhibiting the hallmarks of life. The cell is also a fantastically intricate and complex system: its behaviour is shaped by molecular networks and processes that regulate cellular physiology, and the response of the cell to its environment. This Laureate Fellowship aims to describe and make sense of this complexity mathematically. At this sub-cellular level stochasticity and complex non-linear feedbacks are all perv ....CellMaps for cell fate decision making systems. The cell is the fundamental unit exhibiting the hallmarks of life. The cell is also a fantastically intricate and complex system: its behaviour is shaped by molecular networks and processes that regulate cellular physiology, and the response of the cell to its environment. This Laureate Fellowship aims to describe and make sense of this complexity mathematically. At this sub-cellular level stochasticity and complex non-linear feedbacks are all pervasive. Building on recent advances in mathematics, statistics, theoretical physics, and data science will result in mathematical models of cells, CellMaps, that will generate mechanistic insights into the fundamental dynamical processes underlying cell fate decision making and differentiation. Read moreRead less
Increasing the efficiency and interpretability of stepped wedge trials. Stepped wedge cluster randomised trials are increasingly being used to test interventions, across many disciplines. This project aims to develop highly efficient trial designs and new methods for the estimation of causally interpretable effects when adherence to interventions is not perfect. This project expects to generate new design types that reduce resources required to test interventions, and methods to understand how t ....Increasing the efficiency and interpretability of stepped wedge trials. Stepped wedge cluster randomised trials are increasingly being used to test interventions, across many disciplines. This project aims to develop highly efficient trial designs and new methods for the estimation of causally interpretable effects when adherence to interventions is not perfect. This project expects to generate new design types that reduce resources required to test interventions, and methods to understand how these interventions work. Expected outcomes include tools to help researchers develop cheaper and more appealing trials, tools to estimate causal effects, the methodology underpinning these tools, and new collaborations. This should provide significant benefits by allowing more interventions to be tested and understood.Read moreRead less
Quantum algebras with supersymmetries. The project aims to make fundamental advances in the theory of quantum algebras. It will develop explicit
structure and representation theory of major classes of quantum algebras which are of great importance to
quantum field theory and integrable models with supersymmetries. The intended outcomes include a solution of
the outstanding classification problem for representations of quantum algebras with supersymmetries, which has
remained open for the last tw ....Quantum algebras with supersymmetries. The project aims to make fundamental advances in the theory of quantum algebras. It will develop explicit
structure and representation theory of major classes of quantum algebras which are of great importance to
quantum field theory and integrable models with supersymmetries. The intended outcomes include a solution of
the outstanding classification problem for representations of quantum algebras with supersymmetries, which has
remained open for the last two decades. It will involve newly-developed methods within the theory of quantum
groups, and both the methods and classification will bring new mathematical instruments for the advance of
supesymmetric conformal field theory and soliton spin chain models.Read moreRead less
Precision ecology: the modern era of designed experiments in plant ecology. This project aims to develop the field of precision ecology, forging a new era of designed experiments where sampling is informed by research questions and what is known about the ecological process being studied. Through the development of novel statistical methods, new experiments globally will be designed to answer important ecological questions including what influence abiotic and biotic factors have on plant commun ....Precision ecology: the modern era of designed experiments in plant ecology. This project aims to develop the field of precision ecology, forging a new era of designed experiments where sampling is informed by research questions and what is known about the ecological process being studied. Through the development of novel statistical methods, new experiments globally will be designed to answer important ecological questions including what influence abiotic and biotic factors have on plant communities over time and different spatial scales. Expected outcomes include new methods and tools that will modernise how future experiments will be conducted in plant ecology. This will provide significant transdisciplinary benefits including new statistical methods that target scientific discovery in ecological studies.Read moreRead less
Principled statistical methods for high-dimensional correlation networks. This project aims to develop a novel and principled approach for building correlation networks. Correlation networks aim to identify the most significant associations present in modern massive datasets, and have numerous applications, ranging from the biomedical and environmental sciences to the social sciences. Nodes of such networks represent features, and edges represent associations, or the lack thereof. Current method ....Principled statistical methods for high-dimensional correlation networks. This project aims to develop a novel and principled approach for building correlation networks. Correlation networks aim to identify the most significant associations present in modern massive datasets, and have numerous applications, ranging from the biomedical and environmental sciences to the social sciences. Nodes of such networks represent features, and edges represent associations, or the lack thereof. Current methods are not readily scalable to modern ultra-high dimensional settings, and do not account for uncertainty in the estimated associations. This project will develop a principled, highly scalable methodology for building such networks, which incorporates uncertainty quantification. Emphasis is placed on modern ultra-high dimensional settings in which differentiating a true correlation from a spurious one is a notoriously difficult task.Read moreRead less