News/Events Australia

Seminar on Risk profiling of pathogens using -omics and AI – 6 February in Melbourne

6 February

Peter Doherty Institute in Melbourne

From 12.00AM

Join the Research Seminar focusing on

Risk profiling of pathogens using -omics and AI technologies

by

Professor Adrian Egli

Director, Institute of Medical Microbiology

University of Zurich

 

This event is part of the University of Melbourne’s Department of Microbiology and Immunology seminar series.

Free registration: https://events.unimelb.edu.au/biomedical-sciences/event/44554-dmi-research-seminar-professor-adrian-egli

 

Abstract:

The integration of advanced -omics technologies and artificial intelligence (AI) is transforming the field of microbiology, offering unprecedented opportunities for pathogen risk profiling and virulence prediction. In this talk, I will explore the use of MALDI-TOF mass spectrometry for rapid phenotypic identification and its novel application in virulence prediction through AI-driven analysis. By leveraging machine learning models trained on vast datasets, we aim to bridge the gap between routine diagnostics and molecular epidemiology, enabling early identification of high-risk strains. Additionally, I will discuss how these approaches, complemented by whole genome sequencing and advanced bioinformatics tools, are being used to understand the dynamics of antimicrobial resistance and pathogen adaptability. These advancements not only enhance diagnostic precision but also pave the way for proactive public health interventions, ultimately improving outcomes in infectious disease management.

Adrian Egli’s Biography:

Adrian’s work stands at the forefront of medical microbiology as the Director of the Institute of Medical Microbiology at the University of Zurich. With an illustrious career rooted in a profound understanding of host-pathogen interactions, his research ambitiously leverages cutting-edge technologies, including genome sequencing, mass spectrometry, and advanced data analysis through bioinformatics and machine learning. His innovative approach aims to revolutionize the diagnosis, treatment, and prevention of infectious diseases, underscoring his commitment to advancing medical science and healthcare outcomes.