Creating subject-specific mathematical models to understand the brain. This project aims to develop a mathematical framework that bridges the different scales of brain activities to provide a new tool for understanding the brain. Methods will be developed that unify individual neural activity with large scale brain activity. The approach will be validated by comparing predictions of interconnected models of neural populations (called mean-field models) to experimental data. The creation of subje ....Creating subject-specific mathematical models to understand the brain. This project aims to develop a mathematical framework that bridges the different scales of brain activities to provide a new tool for understanding the brain. Methods will be developed that unify individual neural activity with large scale brain activity. The approach will be validated by comparing predictions of interconnected models of neural populations (called mean-field models) to experimental data. The creation of subject-specific models from data is important, as there is large variability in neural circuits between individuals despite seemingly similar network activity. The intended outcome is new insights into the processes that govern brain function and methods for improving functional imaging of, and interfacing to, the brain.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL210100110
Funder
Australian Research Council
Funding Amount
$3,021,288.00
Summary
New Approaches to Understand How Form and Function Shape Complex Systems. As biology and medicine transform into quantitative sciences, existing mathematical methods are often inadequate to explain the data they generate. This project aims to unlock the potential of such biomedical data through the development of new mathematical approaches that combine concepts from pure and applied mathematics, statistics and data science, and then to investigate their ability to generate mechanistic insight i ....New Approaches to Understand How Form and Function Shape Complex Systems. As biology and medicine transform into quantitative sciences, existing mathematical methods are often inadequate to explain the data they generate. This project aims to unlock the potential of such biomedical data through the development of new mathematical approaches that combine concepts from pure and applied mathematics, statistics and data science, and then to investigate their ability to generate mechanistic insight into fundamental biomedical processes. In this way, the project expects to affect a paradigm shift in mathematical biology while strengthening Australia’s reputation as a world-leader in mathematical biology. An outcome from this project could be new mathematical models that guide decision making in the clinic.Read moreRead less
Mathematical models of 4D multicellular spheroids. Mathematical models have a long, successful history of providing biological insight, and new mathematical models must be developed to keep pace with emerging technologies. Modern experimental procedures involve studying 3D multicellular spheroids with fluorescent labels to show both the location of cells and the cell cycle progression. This 4D data (3D spatial information + cell cycle time) provides vast information. No mathematical models ha ....Mathematical models of 4D multicellular spheroids. Mathematical models have a long, successful history of providing biological insight, and new mathematical models must be developed to keep pace with emerging technologies. Modern experimental procedures involve studying 3D multicellular spheroids with fluorescent labels to show both the location of cells and the cell cycle progression. This 4D data (3D spatial information + cell cycle time) provides vast information. No mathematical models have been specifically developed to interpret/predict 4D spheroids. This project will deliver the first high-fidelity mathematical models to interpret/predict 4D spheroid experiments in real time, providing quantitative insight into innate mechanisms and responses to various intervention treatments. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100097
Funder
Australian Research Council
Funding Amount
$389,670.00
Summary
Mathematical models for actin scavenging and biofilm removal. The project aims to develop mathematical models for actin scavenging and biofilm removal, processes that combine to alleviate tissue damage and inflammation. Actin scavenging eliminates the protein F-actin which is released during cell death, but this process is not fully-understood. Biofilms are colonies of micro-organisms, for example bacteria, that are highly resistant to antimicrobial treatment. This project expects to generate ne ....Mathematical models for actin scavenging and biofilm removal. The project aims to develop mathematical models for actin scavenging and biofilm removal, processes that combine to alleviate tissue damage and inflammation. Actin scavenging eliminates the protein F-actin which is released during cell death, but this process is not fully-understood. Biofilms are colonies of micro-organisms, for example bacteria, that are highly resistant to antimicrobial treatment. This project expects to generate new knowledge, using an innovative combination of mathematical modelling and cell biology experiments. Expected outcomes include new theory and software, yielding the benefits of increased understanding of cell biology, and potential to enhance development of smart materials that eliminate biofilms.Read moreRead less
Advances in data integration modelling for infectious disease response. This project aims to develop powerful mathematical frameworks that integrate data from multiple sources to facilitate informed decisions in response to the threat of present, and future, infectious diseases. The project expects to generate new knowledge in mathematics by advancing the tools for incorporating multiple data sources into models of infectious diseases. The expected outcomes include enhanced capacity to predict s ....Advances in data integration modelling for infectious disease response. This project aims to develop powerful mathematical frameworks that integrate data from multiple sources to facilitate informed decisions in response to the threat of present, and future, infectious diseases. The project expects to generate new knowledge in mathematics by advancing the tools for incorporating multiple data sources into models of infectious diseases. The expected outcomes include enhanced capacity to predict spatiotemporal changes in transmission of infectious diseases. This project should provide significant benefits in the advancement of modelling techniques broadly applicable to infectious disease settings, which will be demonstrated for antimalarial drug resistance – a major threat to malaria elimination.
Read moreRead less
Hypergraph models for complex discrete systems. This project aims to better understand the structure and properties of very large hypergraphs of various kinds. Hypergraphs are very general mathematical objects which can be used to model complex discrete systems. They arise naturally in many areas such as ecology, chemistry and computer science. Despite this, our theoretical understanding of very large, or random, hypergraphs lags far behind the intensely-studied special case of graphs. This proj ....Hypergraph models for complex discrete systems. This project aims to better understand the structure and properties of very large hypergraphs of various kinds. Hypergraphs are very general mathematical objects which can be used to model complex discrete systems. They arise naturally in many areas such as ecology, chemistry and computer science. Despite this, our theoretical understanding of very large, or random, hypergraphs lags far behind the intensely-studied special case of graphs. This project will answer many fundamental questions about large, random hypergraphs. The expected outcomes of the project also include new tools for working with hypergraphs, such as efficient algorithms for sampling hypergraphs. These outcomes will benefit researchers who use hypergraphs in their work and will enhance Australia's reputation for research in this area.Read moreRead less
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
Determining features that separate groups of protein sequences. This project aims to develop mathematical approaches for determining features that distinguish one group of proteins from another, based on their amino acid sequences. The groups of sequences will reflect different outcomes, so that identifying the fundamental features can result in targeted interventions against the poorer outcome. A simple comparison at each position or of known features can fail to determine robust differentiator ....Determining features that separate groups of protein sequences. This project aims to develop mathematical approaches for determining features that distinguish one group of proteins from another, based on their amino acid sequences. The groups of sequences will reflect different outcomes, so that identifying the fundamental features can result in targeted interventions against the poorer outcome. A simple comparison at each position or of known features can fail to determine robust differentiators and so more complex methods are required. The project will, for example, help identify HIV vaccine targets by comparing early HIV transmission sequences from those in chronic infection. The methods will be applicable to viral proteins where high mutation rates make this task even more complex.Read moreRead less