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
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
Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising ap ....Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising approach, but its accuracy is far from satisfactory. The software systems developed in this project will be used in structural identification of target proteins in drug design. This will make drug design process more efficient, saving time and cost, potentially saving lives.Read moreRead less
RNA structure prediction by deep learning and evolution-derived restraints. This project addresses the long-standing structure-folding problem of Ribonucleic acids (RNA) whose solution is essential for elucidating the roles of noncoding RNAs in living organisms. The proposed approach will detect hidden homologous sequences and enhance evolutionary covariation signals by developing new algorithms for search and smarter neural networks for deep learning. The project expects to generate new tools ....RNA structure prediction by deep learning and evolution-derived restraints. This project addresses the long-standing structure-folding problem of Ribonucleic acids (RNA) whose solution is essential for elucidating the roles of noncoding RNAs in living organisms. The proposed approach will detect hidden homologous sequences and enhance evolutionary covariation signals by developing new algorithms for search and smarter neural networks for deep learning. The project expects to generate new tools for structure-based probing of RNA evolutional and functional mechanisms. The outcomes should provide significant benefits by high-accuracy computational modelling of RNA structures that are difficult and costly to solve by current structural biology techniques but important for enabling biotech and clinical applications.Read moreRead less