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Using AI to predict the outcome of infection and future evolution of Ebola virus and SARS-CoV-2

Using AI to predict the outcome of infection and future evolution of Ebola virus and SARS-CoV-2

By Professor Julian Hiscox, Chair in Infection and Global Health at the University of Liverpool and deputy associate pro-vice chancellor for research and Impact. 

Abstract

Julian’s research group has been at the forefront of two major outbreaks – the West African Ebola outbreak (where they were members of the European Mobile Laboratory in Guinea) and the COVID-19 pandemic. The seminar will discuss the analysis of clinical samples from patients with Ebola virus disease (EVD) and COVID-19 using RNA sequencing – both Illumina and Oxford Nanopore. By analysing the sequencing data, transcriptomic approaches were used to investigate the response to infection in people and animal models and inform functional biology. This focused on two areas rooted in AI/machine learning approaches. The first being able to predict the outcome of infection and the second developing algorithms to predict the future evolution of SARS-CoV-2 and how these feed into designing and planning future vaccines measures.

Bio

Julian Hiscox is Chair in Infection and Global Health at the University of Liverpool and also a deputy associate pro-vice chancellor for research and Impact. He has a BSc in Genetics from University College London and a PhD from the Pirbright Institute/University of Reading. His research group, composed of 6 PDRAs and 10 PhD students, is underpinned by $10M contract funding from the US Food and Drug Administration to characterise SARS-CoV-2 and MERS-CoV with relevance to medical countermeasures. Due to his coronavirus expertise, during the COVID-19 pandemic, Julian was a co-opted member of the New and Emerging Respiratory Virus Threats Advisory Group (NERVTAG), and a participant at the Scientific Advisory Group for Emergencies (SAGE) – advisory groups to UK Government. He is a current member of NERVTAG.

Invited seminarProf. Arnab Pain

Event Quick Information

Date
01 Oct, 2023
Time
03:00 PM - 04:00 PM
Venue
Building 2 - Level 5 - Room 5209