Discovery Early Career Researcher Award - Grant ID: DE130100614
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Novel statistical algorithms and methods to quantify and partition pleiotropy between complex traits in populations. A fundamental question in biology is how common genetic effects are shared between traits or groups. For example, is cognition or human behaviour genetically identical across genders or across human population groups? This project will address these questions using multiple independent genome-wide association studies.
Enabling Molecular Plant Breeding for Drought Adaptation Using Genome-to-Phenome Modelling Technologies. Effective molecular plant breeding for improved water productivity of sorghum would generate significant economic and social benefits for rural communities in NE Australia. There is a significant opportunity to expand the sorghum industry in the region. Despite the global financial crisis, global demand for meat continues to increase, generating strong demand from intensive livestock industri ....Enabling Molecular Plant Breeding for Drought Adaptation Using Genome-to-Phenome Modelling Technologies. Effective molecular plant breeding for improved water productivity of sorghum would generate significant economic and social benefits for rural communities in NE Australia. There is a significant opportunity to expand the sorghum industry in the region. Despite the global financial crisis, global demand for meat continues to increase, generating strong demand from intensive livestock industries for feed grain. Price is projected to return to high levels given continuing use of major feed grains for biofuel. A 10% increase in sorghum production would add net value of $48M annually, much via employment. The scientific content of this project positions Australia at the leading edge globally in this emerging research field. Read moreRead less
Estimating genotype-environment interaction using genomic information. This project aims to develop statistical methods that can explore genotype–environment interaction at the genomic level using genome-wide single nucleotide polymorphisms or sequence data. It plans to estimate how the effects of genetic variants change with changing environmental conditions and how overall genetic variance changes due to changing effects in specific gene regions. It plans to deliver statistical models and meth ....Estimating genotype-environment interaction using genomic information. This project aims to develop statistical methods that can explore genotype–environment interaction at the genomic level using genome-wide single nucleotide polymorphisms or sequence data. It plans to estimate how the effects of genetic variants change with changing environmental conditions and how overall genetic variance changes due to changing effects in specific gene regions. It plans to deliver statistical models and methods and an efficient algorithm implemented in software, which would broadly benefit the field of complex trait genetics. Methods to estimate genotype–environment interaction effects at the genomic level would help elucidate complex biological systems, including human genetic response to changing environmental factors and the potential adaptation of animals to changing environmental conditions.Read moreRead less
Whole-genome multivariate reaction norm model for complex traits. This project aims to develop a multivariate whole-genome genotype-covariate correlation and interaction model that can be applied to a wide range of existing genome-wide association study (GWAS) datasets. Genotype-covariate correlation and interaction (GCCI) are fundamental in biology but there is no standard approach to disentangle interaction from correlation in the whole-genome analyses. This project will address the key featur ....Whole-genome multivariate reaction norm model for complex traits. This project aims to develop a multivariate whole-genome genotype-covariate correlation and interaction model that can be applied to a wide range of existing genome-wide association study (GWAS) datasets. Genotype-covariate correlation and interaction (GCCI) are fundamental in biology but there is no standard approach to disentangle interaction from correlation in the whole-genome analyses. This project will address the key feature in biology, which relates to dissecting the complex mechanism of association and interaction. The proposed statistical model implemented in a context of a novel design based on multiple GWAS data sets is a paradigm shifting-tool with applications to multiple industries.Read moreRead less
Effective software vulnerability detection for web services. This project aims to design and implement new and better methods to find vulnerabilities in software services delivered over the web or through the cloud, as well as methods for proving the absence of certain types of vulnerability. So-called injection attacks are pervasive and generally considered the most important security threat on today's Internet. The programming languages used for software services tend to use strings as a unive ....Effective software vulnerability detection for web services. This project aims to design and implement new and better methods to find vulnerabilities in software services delivered over the web or through the cloud, as well as methods for proving the absence of certain types of vulnerability. So-called injection attacks are pervasive and generally considered the most important security threat on today's Internet. The programming languages used for software services tend to use strings as a universal data structure, which unfortunately makes it hard to separate trusted code from untrusted user-provided data. This project intends to develop novel program analysis tools and string constraint solvers, and employ these tools to support sophisticated automated reasoning about string manipulating software.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220101210
Funder
Australian Research Council
Funding Amount
$451,634.00
Summary
Deciphering molecular genetic mechanisms underlying chromatin interactions. This project aims to generate the high confidence map of enhancer-promoter links in 61 tissues and cells through robust integration of novel machine learning tools with genomic and epigenomic datasets. Understanding which key elements in the genome may be important to fine-tune gene expression is essential for understanding biological pathways. The expected outcomes include i) New tools to robustly identify true chromati ....Deciphering molecular genetic mechanisms underlying chromatin interactions. This project aims to generate the high confidence map of enhancer-promoter links in 61 tissues and cells through robust integration of novel machine learning tools with genomic and epigenomic datasets. Understanding which key elements in the genome may be important to fine-tune gene expression is essential for understanding biological pathways. The expected outcomes include i) New tools to robustly identify true chromatin pairs; ii) Comperehensive maps of regulatory interactomes in 61 tissues & cells, which will provide a roadmap for interpreting & prioritising noncoding variants.
This should provide significant benefit to Australia's capacity for cutting-edge genomics research through fundamental understanding of gene regulation mechanism.Read moreRead less
Human interaction with context-aware computing systems. Context-aware systems can provide seamless support of IT applications in a variety of technologies and therefore can improve: (i) work performance and adoption of IT in many industries; and (ii) the quality of life through better support for health services, education, and everyday tasks. Currently proposed solutions for context-aware systems fail to deliver systems which are usable for non-IT professionals. The proposed project will show h ....Human interaction with context-aware computing systems. Context-aware systems can provide seamless support of IT applications in a variety of technologies and therefore can improve: (i) work performance and adoption of IT in many industries; and (ii) the quality of life through better support for health services, education, and everyday tasks. Currently proposed solutions for context-aware systems fail to deliver systems which are usable for non-IT professionals. The proposed project will show how to design context-aware systems that are usable and whose autonomic decisions can be trusted. Additional benefits include increased scientific competitiveness of Australia, strengthened collaboration with international research institutions, and high quality graduates (PhDs, Masters, Honours).Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0347131
Funder
Australian Research Council
Funding Amount
$115,490.00
Summary
Intelligent Computer System to Access Information Directly from the Brain Using High Resolution Electroencephalography and Repetitive Transcranial Magnetic Stimulation. The ambitious aim of this project is to create a novel intelligent computer system which accesss information from the brain. To do this we use repetitive Transcranial Magnetic Stimulation and high resolution Electroencephalography.
3D Diffusion Models for Generating and Understanding 3D Scenes. Diffusion models, such as DALL-E2 and Imagen, have achieved remarkable success in generating photorealistic images and hold promise to solve long-standing computer vision problems. However, 3D scene generation remains unexplored. This research project aims to bridge the gap by developing 3D diffusion models capable of generating complete 3D scenes. This will advance our theoretical understanding of diffusion in complex 3D environmen ....3D Diffusion Models for Generating and Understanding 3D Scenes. Diffusion models, such as DALL-E2 and Imagen, have achieved remarkable success in generating photorealistic images and hold promise to solve long-standing computer vision problems. However, 3D scene generation remains unexplored. This research project aims to bridge the gap by developing 3D diffusion models capable of generating complete 3D scenes. This will advance our theoretical understanding of diffusion in complex 3D environments and open up new possibilities for applications in fields such as virtual reality, architecture, and city planning. The proposed 3D diffusion models will also enhance the accuracy of computer vision tasks related to 3D scene understanding, such as object detection, tracking, and semantic segmentation.Read moreRead less
MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) ne ....MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) new methods for susceptibility diagnosis, 3) new defences that leverage privacy and utility. Data-oriented services are estimated to be valuable assets in the future. These techniques can help Australia gain cutting edge advantage in machine learning security and privacy and protect its intellectual property on these services.Read moreRead less