Global Collaborations and Interpretable Data Accelerate Health and Medical Research


Our genome holds the secrets about our future disease risks and how to optimally treat diseases we already have. Handling this data is complex due to its sheer size but machine learning and Cloud computing are a game-changer, helping us to uncovered many of these secrets for the first time. However, such insights are only possible with global collaborations and the analysis of mega-biobank data.

This talk outlines the CSIRO developed software solutions, which use the latest in cloud architecture, machine learning and distribution channels to support a wide range of digital health applications; from disease gene detection, to personalized gene therapy; from pathogen diagnostics to biosecurity applications. Specifically, we developed novel bioinformatics approaches to track viral evolution that has led to the first study on vaccine efficacy for the different COVID-19 virus strains. We also developed a novel machine learning framework capable of processing one trillion genomic datapoints to detect disease genes in motor neuron disease and cardiovascular disease. The talk concludes by looking into the future of how clinical ontologies (FHIR) in combination with health-specific cloud deployment (marketplaces) accelerates human health research and ultimately clinical practice.


Dr Denis Bauer is an internationally recognised expert in artificial intelligence, who is passionate about improving health by understanding the secrets in our genome using cloud-computing technology. She is CSIRO’s Principal Research Scientist in transformational bioinformatics and adjunct associate professor at Macquarie University. She keynotes international IT, LifeScience and Medical conferences and is an AWS Data Hero, determined to bridge the gap between academe and industry. To date, she has attracted more than $31M to further health research and digital applications. Her achievements include developing open-source bioinformatics software to detect new disease genes and developing computational tools to track, monitor and diagnose emerging diseases, such as COVID-19.

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