Visual Analytics for Next Generation Sequencing. Next-generation sequencing technologies have brought a revolution in biology and healthcare, while taxing the ability of scientists and clinicians to identify and process relevant data, to make sense of it all and communicate it to others in a concise and meaningful way. This project aims to tackle this problem through fundamentally new approaches to data selection and visualisation at very large scale, actively encoding for insight into underlyin ....Visual Analytics for Next Generation Sequencing. Next-generation sequencing technologies have brought a revolution in biology and healthcare, while taxing the ability of scientists and clinicians to identify and process relevant data, to make sense of it all and communicate it to others in a concise and meaningful way. This project aims to tackle this problem through fundamentally new approaches to data selection and visualisation at very large scale, actively encoding for insight into underlying biological and biomedical processes, bringing sustainable discovery of new relationships and variations within the data. The project aims to support new approaches to medical diagnosis and treatment, and offer crucial lessons to address the broader challenge of understanding large, complex data sets.Read moreRead less
Next-generation genomic resources to tackle parasitic diseases of animals. The revolution in genomics provides unprecedented opportunities to tackle destructive parasitic diseases affecting billions of animals worldwide. Through a synergy of leading-edge technologies and a strong partnership with BGI International, this project aims to deliver major conceptual advances in the understanding of parasitism; an unparalleled skills-base in genomics and bioinformatics; innovative new molecular technol ....Next-generation genomic resources to tackle parasitic diseases of animals. The revolution in genomics provides unprecedented opportunities to tackle destructive parasitic diseases affecting billions of animals worldwide. Through a synergy of leading-edge technologies and a strong partnership with BGI International, this project aims to deliver major conceptual advances in the understanding of parasitism; an unparalleled skills-base in genomics and bioinformatics; innovative new molecular technologies; and new treatments and diagnostic tests as biotechnological outcomes. This leap forward in Australia will substantially enhance the global profile of parasitology research, training and employment opportunities for early career scientists, and improve access to international research funding and networks. Read moreRead less
Efficient data mining methods for evidence-based decision making. This project aims to develop efficient data mining methods for causal predictions. Evidence-based decision making (EBD), such as evidence-based medicine and policy, is always preferable. To support EBD, causal predictions forecast how outcomes change when conditions are manipulated. Progress has been made in theoretical research on causal inference based on observational data, but few methods can automatically mine causal signals ....Efficient data mining methods for evidence-based decision making. This project aims to develop efficient data mining methods for causal predictions. Evidence-based decision making (EBD), such as evidence-based medicine and policy, is always preferable. To support EBD, causal predictions forecast how outcomes change when conditions are manipulated. Progress has been made in theoretical research on causal inference based on observational data, but few methods can automatically mine causal signals from the data and methods for efficient causal predictions based on data are even fewer. This project will apply its methods to biomedical problems. The outcomes could support smart and data-driven evidence based decision making in many areas, such as therapeutics and government policy making.Read moreRead less
Smart algorithms for visual field assessment. Australian demographic studies show that visual impairment contributes significantly to elderly disability. Visual field loss due to glaucoma, the second leading cause of blindness in developed nations, may be slowed if detected early, but recent studies estimate 50% of Australians with glaucoma are undiagnosed. The fast and effective approaches to measuring visual fields discovered in this project will allow more accurate diagnosis and monitoring of ....Smart algorithms for visual field assessment. Australian demographic studies show that visual impairment contributes significantly to elderly disability. Visual field loss due to glaucoma, the second leading cause of blindness in developed nations, may be slowed if detected early, but recent studies estimate 50% of Australians with glaucoma are undiagnosed. The fast and effective approaches to measuring visual fields discovered in this project will allow more accurate diagnosis and monitoring of vision loss; crucial for the ARC's priority goals of "ageing well, ageing productively" and "preventative healthcare". Developing smart algorithms in conjunction with Heidelberg Engineering creates an opportunity for the international promotion of Australia's biomedical software capabilities.Read moreRead less
Real-time phylogenetics for food-borne outbreak surveillance. The project aims to introduce, for the first time, real-time evolutionary analysis of agricultural pathogens so that outbreaks affecting crops and the food supply can be managed precisely and rapidly. An expert team will implement a large-scale data analytics framework in user-friendly software that integrates Australian infectious disease genomics data with global data. Underpinning this work are new theory and algorithms that apply ....Real-time phylogenetics for food-borne outbreak surveillance. The project aims to introduce, for the first time, real-time evolutionary analysis of agricultural pathogens so that outbreaks affecting crops and the food supply can be managed precisely and rapidly. An expert team will implement a large-scale data analytics framework in user-friendly software that integrates Australian infectious disease genomics data with global data. Underpinning this work are new theory and algorithms that apply Sequential Monte Carlo to update phylogenetic analyses continuously as new data arrives. Expected outcomes include new knowledge of statistical algorithms for evolutionary analysis, relevant to biological disciplines beyond infectious disease; and enhanced capacity for infectious disease analysis. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190100491
Funder
Australian Research Council
Funding Amount
$418,386.00
Summary
Linking genomic changes to the generation of biodiversity. This project aims to provide a suite of theories, methods and software to enhance our understanding on how the generation of variation at molecular level is linked to the generation of species richness at lineage level. This new approach tests various ways that molecular changes are manifested as patterns of diversification, as revealed by genomic data analysed at the lineage level in phylogenetic studies. Expected outcomes of this proje ....Linking genomic changes to the generation of biodiversity. This project aims to provide a suite of theories, methods and software to enhance our understanding on how the generation of variation at molecular level is linked to the generation of species richness at lineage level. This new approach tests various ways that molecular changes are manifested as patterns of diversification, as revealed by genomic data analysed at the lineage level in phylogenetic studies. Expected outcomes of this project add to a growing body of evolutionary theory and provide practical phylogenetic tools for future analyses. These should benefit Australia by improving our understanding on the formation of Australia’s biodiversity hotspots.Read moreRead less
Uncovering microRNA decay regulation in mammalian cells. MicroRNAs (miRNAs) constitute a novel mechanism used by cells to regulate gene expression, however, very little is known about the mechanisms affecting miRNA accumulation. Characterisation of the kinetics of miRNA turnover is of paramount importance to establish the reliability of miRNAs as novel biomarkers. This project aims to characterise miRNA stability in mammalian cells, investigate mechanisms of turnover and establish their importan ....Uncovering microRNA decay regulation in mammalian cells. MicroRNAs (miRNAs) constitute a novel mechanism used by cells to regulate gene expression, however, very little is known about the mechanisms affecting miRNA accumulation. Characterisation of the kinetics of miRNA turnover is of paramount importance to establish the reliability of miRNAs as novel biomarkers. This project aims to characterise miRNA stability in mammalian cells, investigate mechanisms of turnover and establish their importance on the regulatory function of miRNAs. Such information is critical in the future development of targeted therapeutics.Read moreRead less
Understanding somatic mutation in plants: new methods, new software, new data. Somatic mutations accumulate as plants grow, affecting everything from short-term ecological interactions to long-term evolutionary dynamics. These mutations have important consequences for plant industry and conservation, but because they are so hard to measure almost nothing is known about them. This project aims to develop new methods and software to detect, analyse, and compare the genome-wide history of somatic m ....Understanding somatic mutation in plants: new methods, new software, new data. Somatic mutations accumulate as plants grow, affecting everything from short-term ecological interactions to long-term evolutionary dynamics. These mutations have important consequences for plant industry and conservation, but because they are so hard to measure almost nothing is known about them. This project aims to develop new methods and software to detect, analyse, and compare the genome-wide history of somatic mutation in individual plants, providing an unprecedented level of detail into an important but understudied source of biological variation. By applying these methods to an iconic experimental population, This project aims to provide the first insights into the genome-wide causes and consequences of somatic mutation in plants.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101323
Funder
Australian Research Council
Funding Amount
$427,098.00
Summary
Structure guided mapping of protein interactions and their perturbation. Protein interactions are central to most biological processes, and significant effort has been devoted to trying to unravel these complicated networks. This project aims to develop new approaches to better understand these interactions, and the consequences of their perturbation. The main expected contributions will be: (i) methods to identify likely protein interaction sites using population conservation; (ii) computationa ....Structure guided mapping of protein interactions and their perturbation. Protein interactions are central to most biological processes, and significant effort has been devoted to trying to unravel these complicated networks. This project aims to develop new approaches to better understand these interactions, and the consequences of their perturbation. The main expected contributions will be: (i) methods to identify likely protein interaction sites using population conservation; (ii) computational approaches to assess the effects of any type of mutation on the interaction; and (iii) an understanding of how disruption of a specific interaction can affect the complicated biological network within a cell. Read moreRead less
Deep correction of DNA sequencing errors by data mining algorithms. This project aims to investigate the many layers of error correction problems in the terabytes of genomic sequence data, and aims to solve these problems by novel data mining algorithms. High-throughput sequencing platforms have generated massive amounts of useful raw data, but also made widespread errors. The new algorithms are capable of correcting errors at deeper layers to further enhance data quality. Expected outcome inclu ....Deep correction of DNA sequencing errors by data mining algorithms. This project aims to investigate the many layers of error correction problems in the terabytes of genomic sequence data, and aims to solve these problems by novel data mining algorithms. High-throughput sequencing platforms have generated massive amounts of useful raw data, but also made widespread errors. The new algorithms are capable of correcting errors at deeper layers to further enhance data quality. Expected outcome includes the knowledge advancement of genomic data industry and interdisciplinary collaboration between biotechnology and data mining. This also provides significant benefit for genomic decisions in forensics and personalised medicine which demand accurate genomic information.Read moreRead less