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We are made up of hundreds of different cell types carrying out a diverse range of functions essential for organism survival. All the information required to specify the morphology, function and response to stimuli of these cells is encoded in identical copies of the genome. The process of gene regu
Current technologies to understand which genes are turned on or off only work on large amounts of biological samples. As a consequence all measurements we receive represent averages across multiple cell types present in the sample. The situation is comparable to studying the contents of a bowl of fr
The Kids Research Institute Australia congratulates Prof Gareth Baynam and Dr Timo Lassmann on their grant over three years from the McCusker Charitable Foundation.
The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual, including phenotypic descriptions, numerical measurements, genetic information, diagnoses, and treatments. A phenopacket can be used as an input file for software that supports phenotype-driven genomic diagnostics and for algorithms that facilitate patient classification and stratification for identifying new diseases and treatments.
Time-critical transcriptional events in the immune microenvironment are important for response to immune checkpoint blockade (ICB), yet these events are difficult to characterise and remain incompletely understood. Here, we present whole tumor RNA sequencing data in the context of treatment with ICB in murine models of AB1 mesothelioma and Renca renal cell cancer.
Our goal was to identify genetic risk factors for severe otitis media (OM) in Aboriginal Australians.
There are an estimated > 400 million people living with a rare disease globally, with genetic variants the cause of approximately 80% of cases. Next Generation Sequencing (NGS) rapidly identifies genetic variants however they are often of unknown significance.
Over 400 million people worldwide are living with a rare disease. Next Generation Sequencing identifies potential disease causative genetic variants. However, many are identified as variants of uncertain significance and require functional laboratory validation to determine pathogenicity, and this creates major diagnostic delays.
People living with rare diseases (PLWRD) still face huge unmet needs, in part due to the fact that care systems are not sufficiently aligned with their needs and healthcare workforce (HWF) along their care pathways lacks competencies to efficiently tackle rare disease-specific challenges. Level of rare disease knowledge and awareness among the current and future HWF is insufficient.
Computer vision technology is advancing rare disease diagnosis to address unmet needs of the more than 300 million individuals affected globally; one in three rare diseases have a known facial phenotype. 3D face model reconstruction is a key driver of these advances.