Decoding miRNA regulated genetic circuits. This project will aim to develop a much better understanding of how the process of making proteins from genes is regulated, and will develop scientific software capable of predicting how a cell will respond to changes in this regulation. The results will have widespread use, including assistance in deciding the best treatments for genetic diseases.
Developing bioinformatics methods for single cell transcriptomics. This project aims to develop novel bioinformatics methods for single cell transcriptomic data that seek to model variability in cell populations. The project expects to generate new approaches using Bayesian statistics that will act as high-end enablers of discovery in transcriptional regulatory processes. Through an interdisciplinary combination of experimental and computational research, insights into fundamental biological pro ....Developing bioinformatics methods for single cell transcriptomics. This project aims to develop novel bioinformatics methods for single cell transcriptomic data that seek to model variability in cell populations. The project expects to generate new approaches using Bayesian statistics that will act as high-end enablers of discovery in transcriptional regulatory processes. Through an interdisciplinary combination of experimental and computational research, insights into fundamental biological processes will be elucidated, specifically the robustness of cellular systems. Expected outcomes include a suite of novel tools that will push the boundaries of current bioinformatics solutions with potential to deliver significant benefits to every domain of biological science, particularly tissue engineering and synthetic biology.Read moreRead less
Understanding prokaryotic small proteins from context. Prokaryotic small proteins are increasingly recognised to play important biological roles but have been largely overlooked due to the lack of adequate tools to study them. This project aims to develop new methods to identify and predict the functions of small proteins from microbial communities by studying sequence patterns in their genomes. These predicted functions will be confirmed in the laboratory, leading to a catalogue of newly charac ....Understanding prokaryotic small proteins from context. Prokaryotic small proteins are increasingly recognised to play important biological roles but have been largely overlooked due to the lack of adequate tools to study them. This project aims to develop new methods to identify and predict the functions of small proteins from microbial communities by studying sequence patterns in their genomes. These predicted functions will be confirmed in the laboratory, leading to a catalogue of newly characterised small proteins from a diverse range of habitats and geographies. By creating new ways to study the role of small proteins in the global microbiome, we will provide the foundational knowledge required to leverage these proteins for use in biotechnology. Read moreRead less
The adaptive evolution of key methane-utilising microorganisms. This project aims to characterise the evolutionary adaptations of a group of microorganisms with a key role in mitigating the release of methane into the atmosphere. Innovative molecular and visualisation-based approaches will be applied to uncover their metabolic diversity and evolutionary history. An important outcome of this study will be the comprehensive understanding of the contribution and impact these microorganisms have on ....The adaptive evolution of key methane-utilising microorganisms. This project aims to characterise the evolutionary adaptations of a group of microorganisms with a key role in mitigating the release of methane into the atmosphere. Innovative molecular and visualisation-based approaches will be applied to uncover their metabolic diversity and evolutionary history. An important outcome of this study will be the comprehensive understanding of the contribution and impact these microorganisms have on the global carbon cycle, which will importantly inform accurate climate change models. This has clear benefits for society, given the precision of such models is essential in our ability to minimise the impact and associated cost of global warming.Read moreRead less
Uncovering new microbial players and processes in the global methane cycle. This project aims to utilise multiple analytical strategies (including metagenomics and metatranscriptomics) to substantially expand our understanding of the key microorganisms, metabolic strategies, and interspecies relationships involved in the formation and consumption of methane. The global methane cycle is controlled by microorganisms that produce and consume this important greenhouse gas, however it is now recognis ....Uncovering new microbial players and processes in the global methane cycle. This project aims to utilise multiple analytical strategies (including metagenomics and metatranscriptomics) to substantially expand our understanding of the key microorganisms, metabolic strategies, and interspecies relationships involved in the formation and consumption of methane. The global methane cycle is controlled by microorganisms that produce and consume this important greenhouse gas, however it is now recognised that there are many as-yet undiscovered methane-metabolising microorganisms in the environment. The project will lead to a greater understanding of the contribution of these novel microorganisms to global carbon cycling and their links to climate change. This will directly benefit modelling efforts to understand future climate change scenarios.Read moreRead less
Statistical Methods for Next Generation Genome-Wide Association Studies. This project aims to develop cutting-edge statistical methods to analyse large genomic datasets and identify genetic variants associated with inter-individual differences in various human traits. Knowledge of trait-associated DNA variants is instrumental in understanding how natural selection has shaped human traits. By integrating genomic data from diverse and underrepresented populations, this project further expects to c ....Statistical Methods for Next Generation Genome-Wide Association Studies. This project aims to develop cutting-edge statistical methods to analyse large genomic datasets and identify genetic variants associated with inter-individual differences in various human traits. Knowledge of trait-associated DNA variants is instrumental in understanding how natural selection has shaped human traits. By integrating genomic data from diverse and underrepresented populations, this project further expects to contribute to the equitable use of genomic technologies in humans, regardless of geographical origins. Expected outcomes of this research include novel analysis methods and software tools, which should broadly and significantly benefit gene discovery in other species, including those of agricultural relevance.Read moreRead less
Exploring the Black Box of Archaeal Methane Metabolism. This project aims to build on new discoveries about how ancient microorganisms belonging to the Archaea that process methane, a significant greenhouse gas. This project expects to generate new data about how these novel Archaea are able to generate/digest methane and other non-methane carbon substrates through metabolic pathways using an interdisciplinary approach. Expected outcomes of this Project include improved techniques to grow these ....Exploring the Black Box of Archaeal Methane Metabolism. This project aims to build on new discoveries about how ancient microorganisms belonging to the Archaea that process methane, a significant greenhouse gas. This project expects to generate new data about how these novel Archaea are able to generate/digest methane and other non-methane carbon substrates through metabolic pathways using an interdisciplinary approach. Expected outcomes of this Project include improved techniques to grow these ancient microorganisms, investigate how they process methane, and understand how they contribute to the global carbon cycle. This will provide significant benefits, such as understanding the how the cycling of methane and non-methane compounds by novel Archaea can be manipulated in anaerobic environments.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.
RNA-based analysis for prediction of islet death in diabetes. Death of insulin-producing cells is a common feature in diabetes. Presently, a blood glucose test remains the only blunt instrument to diagnose diabetes. The RNA-based analysis for prediction of islet death in diabetes (RAPID) study links with eight clinical trials to test this newly developed non-invasive assay for predicting diabetes. Early diagnosis will help to reduce diabetic complications in later life.
Genomics of temperature response in plants. Climate change is predicted to have negative impacts on Australian agriculture. This project will use genomic tools to uncover biological mechanisms for plant response to temperature that will help design crop varieties that are more tolerant to higher temperatures.