SMS scnews item created by Miranda Luo at Thu 30 Mar 2023 1445
Type: Seminar
Distribution: World
Expiry: 3 Apr 2023
Calendar1: 3 Apr 2023 1300-1400
CalLoc1: In person: CPC, Level 6 Mackenzie Seminar Room OR Zoom:
Auth: miranda@ (jluo0722) in SMS-SAML

Judith and David Coffey Seminar Series: Bahlo

Title: Multi-Omics and AI approaches for the study of retinal diseases 

Speaker: Professor Melanie Bahlo (The Walter and Eliza Hall Institute of Medical

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.

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