How Does NF-kB2 Regulate Thymic Selection To Prevent Organ-specific Autoimmune Disease?
Funder
National Health and Medical Research Council
Funding Amount
$787,600.00
Summary
Autoimmune diseases like type 1 diabetes and thyroiditis arise from defects that cause the immune system to confuse self and non-self. Normally, this distinction is programmed in the thymus. We recently identified the gene that causes a form of autoimmune disease. We also made an important discovery about how the thymus gland regulates self-non-self discrimination. We will build on these two discoveries to gain a precise understanding of how the immune system normally avoids autoimmune disease.
Modeling Human Actin Related Protein 2/3 Complex Subunit 1B (ARPC1B) Deficiency In Mice
Funder
National Health and Medical Research Council
Funding Amount
$755,005.00
Summary
The actin cytoskeleton forms the structure that not only keeps cells in their normal shape but is also essential for the movement of cells and for interaction between cells. We have recently identified the first patients with an immunodeficiency caused by a defect in a gene called ARPC1B, which plays a crucial role in the regulation of actin. Through the investigation of novel mouse models we will elucidate the pathomechanism underlying the disease of these patients.
Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a hig ....Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a high theoretical value, as the questions we shall address are of independent interest to pure mathematicians.Read moreRead less
Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a hig ....Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a high theoretical value, as the questions we shall address are of independent interest to pure mathematicians.
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It is feasible to sequence patient genomes but we need to know more about how genetic variants cause complex disease. We have sequenced genomes from patients with immune deficiency and will test the idea that genetic variation causes consistent changes in particular white blood cells, thus providing a bridge between genomic information and clinical diagnosis. Outcomes will include more accurate diagnosis, better understanding of immunity, and a strategy for using whole genome information.
Cohort discovery and activity mining for policy impact prediction. Cohort discovery and activity mining for policy impact prediction. This project aims to develop an intelligent systematic framework to predict policy impacts on Australian patients, by discovering inherent patient cohorts and assessing the impact of the policies on these cohorts. The proposed methods lay the theoretical foundations for building intelligent automated tools for policy assessment. Expected outcomes are data-driven p ....Cohort discovery and activity mining for policy impact prediction. Cohort discovery and activity mining for policy impact prediction. This project aims to develop an intelligent systematic framework to predict policy impacts on Australian patients, by discovering inherent patient cohorts and assessing the impact of the policies on these cohorts. The proposed methods lay the theoretical foundations for building intelligent automated tools for policy assessment. Expected outcomes are data-driven patient group discovery, which could more precisely identify the patient cohorts most likely to benefit from a specific policy; and a model to predict the efficacy of policy options, which could increase the sustainability of the national health system by enabling smarter, more efficient policy decision-making.Read moreRead less
Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an ....Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.Read moreRead less
Methylation-sensitive T Cell Genes And Childhood Food Allergy.
Funder
National Health and Medical Research Council
Funding Amount
$461,232.00
Summary
Australia has the highest reported prevalence food allergy in the world. Despite this, little is known about how allergy develops. Mounting evidence implicates environmentally induced disruption of the genetic blueprint via a process known as epigenetics. We are combining the strengths of food challenge proven food allergy with assessment of immune functioning & cutting edge genomics, to extensively characterise the pathways leading to food allergy in children.
Understanding The Pathogenesis And Heterogeneity Of Autoimmunity As Failure Of Multiple Steps
Funder
National Health and Medical Research Council
Funding Amount
$504,023.00
Summary
Autoimmune diseases like diabetes, thyroid disease or rheumatoid arthritis affect around 1 in 15 people in Australia. It is clear that defects in a number of different genetic mechanisms can contribute to the development of autoimmunity. But it is currently not clear how these different mechanisms need to interact to prevent the onset of disease. This grant seeks to understand these interactions and how defects in two or more tolerance mechanisms can lead to autoimmunity.
Methylation Sensitive Genes And The Transition To Allergic Disease: A Twin Study
Funder
National Health and Medical Research Council
Funding Amount
$493,843.00
Summary
Australia has amongst the highest reported prevalence allergic conditions (including asthma) in the world. Despite this, little is known about how these conditions arise. Mounting evidence implicates environmentally induced disruption of the genetic blueprint via a process known as epigenetics. We are combining the strengths of a unique collection of identical twins where one of a pair is sensitive to house dust mite, with cutting edge genomics, to characterise the pathways leading to allergy in ....Australia has amongst the highest reported prevalence allergic conditions (including asthma) in the world. Despite this, little is known about how these conditions arise. Mounting evidence implicates environmentally induced disruption of the genetic blueprint via a process known as epigenetics. We are combining the strengths of a unique collection of identical twins where one of a pair is sensitive to house dust mite, with cutting edge genomics, to characterise the pathways leading to allergy in children.Read moreRead less