Title: Multi-Omics and AI approaches for the study of retinal diseases Speaker: Professor Melanie Bahlo (The Walter and Eliza Hall Institute of Medical Research) Abstract: The retina, or back of the eye, is a very specialized human tissue with incredible energy demands and a unique metabolism that is still poorly understood. The human eye is also unique in the tree of life, with special adaptations and spatial landmarks only observed in humans and higher primates. Retinal diseases often correspond to such landmarks, for example age-related macular degeneration and macular telangiectasia Type (MacTel) are hallmarks of the macula, a particular part of the retina. In this talk I will summarise our journey into the area of retinal diseases which have helped us to understand MacTel. I will also cover current work on the subset of the UK Biobank cohort with OCT imaging, where we are using our insights to inform retinal biology and disease. About the speaker: Professor Bahlo is the Theme Leader of the "Healthy Development and Ageing" theme at The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia, overseeing the scientific strategy for three divisions, including the Population Health and Immunity division which she co-established in 2015. A bioinformatician/statistical geneticist with over 20 years’ experience, Professor Bahlo’s research aims to understand the genetic basis of human diseases, with a focus on neurological and retinal disorders including epilepsy, ataxia, Parkinson’s disease, Macular Telangiectasia type 2 (MacTel) and Age-related Macular degeneration (AMD). Professor Bahlo’s research lab has developed novel analysis methods and software particularly for identity by descent methods and repeat expansions. Her lab also enjoys working on large cohorts with multi-omic data and is increasingly utilizing AI enabled phenotypes to identify biological mechanisms. This work has led to the identification of the role of many genes in disease and understanding of genetic pathways, also providing genetic diagnoses for many patients.