Stochastic modelling of genetic regulatory networks with burst process. This project will develop the next generation of stochastic modelling to study the fundamental principles of genetic regulation. Simulations will yield deeper insight into the origin of bistability and oscillation in gene networks.
Discovery Early Career Researcher Award - Grant ID: DE210101344
Funder
Australian Research Council
Funding Amount
$364,981.00
Summary
Advancing genomic-driven infectious diseases modelling. Emerging infectious diseases and antimicrobial resistance are among the greatest threats to Australian health and agriculture, and current surveillance tools may fail to detect and mitigate infectious disease outbreaks in real time. This project will develop advanced phylodynamic methods (i.e., mathematical models of infectious disease transmission and pathogen evolution) to enable real-time surveillance of infectious disease outbreaks as t ....Advancing genomic-driven infectious diseases modelling. Emerging infectious diseases and antimicrobial resistance are among the greatest threats to Australian health and agriculture, and current surveillance tools may fail to detect and mitigate infectious disease outbreaks in real time. This project will develop advanced phylodynamic methods (i.e., mathematical models of infectious disease transmission and pathogen evolution) to enable real-time surveillance of infectious disease outbreaks as they emerge and monitor levels of drug resistance.Read moreRead less
An efficient approach to the computation of bacterial evolutionary distance. This project aims to apply advanced mathematical tools to improve our understanding of bacterial evolution. Bacteria account for as much total Earth biomass as all plant species put together, and have an unparalleled ability to evolve quickly and adapt to changing environments. Unfortunately, the existing mathematical models used to model bacterial evolution are generally computationally intractable. This project will r ....An efficient approach to the computation of bacterial evolutionary distance. This project aims to apply advanced mathematical tools to improve our understanding of bacterial evolution. Bacteria account for as much total Earth biomass as all plant species put together, and have an unparalleled ability to evolve quickly and adapt to changing environments. Unfortunately, the existing mathematical models used to model bacterial evolution are generally computationally intractable. This project will rectify this situation by using representation theory to transform combinatorial group theory into linear algebra, allowing for the application of advanced methods of numeric approximation. This will provide a better understanding of how bacteria evolve and improve our ability to manage their impact.Read moreRead less
New methods for integrating population structure and stochasticity into models of disease dynamics. Epidemics, such as the 2007 equine 'flu outbreak and 2009 swine 'flu pandemic, highlight the need to make informed decisive responses. This project will develop new methods that incorporate two important aspects of disease dynamics---host structure and chance---into mathematical models, and determine their impact in terms of controlling infections.
Computational methods for population-size-dependent branching processes. Branching processes are the primary mathematical tool used to model populations that evolve randomly in time. Most key results in the theory are derived under the simplifying assumption that individuals reproduce and die independently of each other. However, this assumption fails in most real-life situations, in particular when the environment has limited resources or when the habitat has a restricted capacity. This project ....Computational methods for population-size-dependent branching processes. Branching processes are the primary mathematical tool used to model populations that evolve randomly in time. Most key results in the theory are derived under the simplifying assumption that individuals reproduce and die independently of each other. However, this assumption fails in most real-life situations, in particular when the environment has limited resources or when the habitat has a restricted capacity. This project aims to develop novel and effective algorithmic techniques and statistical methods for a class of branching processes with dependences. We will use these results to study significant problems in the conservation of endangered island bird populations in Oceania, and to help inform their conservation management.Read moreRead less
Multiscale models in immuno-epidemiology. The spread of a pathogen (for example, a virus or bacteria) through a population is a multi-scale phenomena, influenced by factors acting at both the population and within-host scales. At the population scale, transmission is influenced by how infectious an infected host is. Infectiousness in turn depends on the balance between pathogen replication within the host and immune/drug control mechanisms. This project aims to develop new mathematical framework ....Multiscale models in immuno-epidemiology. The spread of a pathogen (for example, a virus or bacteria) through a population is a multi-scale phenomena, influenced by factors acting at both the population and within-host scales. At the population scale, transmission is influenced by how infectious an infected host is. Infectiousness in turn depends on the balance between pathogen replication within the host and immune/drug control mechanisms. This project aims to develop new mathematical frameworks for simultaneously modelling these two scales. This will provide a platform for the rigorous study of complex biological interactions - such as the emergence and combat of drug-resistance - that shape society's ability to control infectious diseases in human, animal and plant systems.Read moreRead less
New Approaches to Modelling and Analysing Long-Memory Random Processes. The project aims to develop new approaches using infinite-dimensional Markov processes to solving important long-standing problems from the theory of long memory random processes and their applications. It aims to: construct a class of new representations of random processes; derive inequalities for the key numerical characteristics; and, devise and investigate numerical methods for computing the characteristics and for perf ....New Approaches to Modelling and Analysing Long-Memory Random Processes. The project aims to develop new approaches using infinite-dimensional Markov processes to solving important long-standing problems from the theory of long memory random processes and their applications. It aims to: construct a class of new representations of random processes; derive inequalities for the key numerical characteristics; and, devise and investigate numerical methods for computing the characteristics and for performing statistical inference on the long memory models. The accuracy of numerical approximations will be analysed using simulations on supercomputers. Expected outcomes include models and results of practical importance with applications such as intrusion detection problems, cell motility for biological data and telecommunication.Read moreRead less
Stochastic modelling of telomere length regulation in ageing research. This project will design innovative stochastic models to explore the molecular mechanisms governing telomere length regulation and their critical roles in determining cell fate. Computer simulations will provide testable predictions regarding the crucial functions of noise in generating the heterogeneity of telomere length.
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
Stochastic populations: theory and applications. The project aims to study models of evolution and cancer development. It will produce new mathematical results and open up new applications of advanced modern mathematical analysis that can be used by evolutionary biologists and cancer researchers, in particular for the understanding of radiation on cell motility.