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
Reconstructing proteins to explain and engineer biological diversity. The aim of this project is to develop computational methods to construct entirely new proteins. Computational reconstruction of enzymes that have been extinct for over 400 million years has revealed remarkable opportunities for biotechnological innovation. The intended outcomes are to develop bioinformatics methods to broaden the scope of ancestral protein reconstruction to include protein super-families, to establish what spe ....Reconstructing proteins to explain and engineer biological diversity. The aim of this project is to develop computational methods to construct entirely new proteins. Computational reconstruction of enzymes that have been extinct for over 400 million years has revealed remarkable opportunities for biotechnological innovation. The intended outcomes are to develop bioinformatics methods to broaden the scope of ancestral protein reconstruction to include protein super-families, to establish what specific changes led to the evolutionary success of a protein, and to re-run evolution to generate proteins that perform in conditions suitable for industrial and agricultural applications, in particular the production of hydroxylated fatty acids for bioplastics. By examining proteins from many life forms, the project plans to develop a novel bioinformatics strategy to understand their evolution and engineer new proteins for use in production of chemical commodities.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
Elucidating the genetics of attention deficit hyperactivity disorder by integrating pathway and prediction analyses. Attention deficit hyperactivity disorder (ADHD) is the most common psychiatric disorder in children; while treatments are available they are ineffective for many patients. This project will develop methods for predicting genetic effects at the level of the biological mechanism to assist in identifying new drug targets and behavioural interventions.