Immune mediated inflammatory diseases (IMIDs) are a diverse and debilitating group of diseases, including Rheumatoid Arthritis, Psoriasis, Lupus and Crohn’s disease. Although IMIDs may appear clinically very different, they share similar patterns of immune dysregulation, which is reflected in common therapeutic strategies targeting cytokines and other immune modulators. Understanding of the immune dysregulation in IMIDS has been revolutionised by 'omics (for example, genomics, proteomics, metabolomics), offering a high dimensional picture of the complex and confounding processes that occur during disease initiation and progression.
However, the ability to study IMIDs across multi-omic dimensions also presents challenges, underscoring the need for tools and infrastructure to enable data integration and analysis and Machine Learning and AI methods to make sense of it. We are using a combination of TranSMART Data warehouses ([ Ссылка ]) and R Shiny (an R package) to present and share multi-omic IMID data, while Machine Learning and AI are bringing new insights into the IMID molecular landscape and therapies. We discuss the impact of these findings on disease understanding and clinical translation.
HDR UK Seminar Series: June 2020
Professor Michael R Barnes
Professor of Bioinformatics, Centre for Translational Bioinformatics, William Harvey Research Institute, Queen Mary University of London
Co-Investigator, Health Data Research-UK London site
Research Fellow, Alan Turing Institute
Related links:
Centre for Translational Bioinformatics, Queen Mary University of London: [ Ссылка ]
Health Data Research (HDR) UK: [ Ссылка ]
HDR UK London site: [ Ссылка ]
Alan Turing Institute: [ Ссылка ]
