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VERSION:2.0
PRODID:-//University of Liverpool Computer Science Seminar System//v2//EN
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DTSTAMP:20261024T172758Z
UID:Seminar-pizza-1232@lxserverM.csc.liv.ac.uk
ORGANIZER:CN=Qiyi Tang:MAILTO:Qiyi.Tang@liverpool.ac.uk
DTSTART:20240301T140000
DTEND:20240301T150000
SUMMARY:Friday Lunch and Talk Series
DESCRIPTION:Maya Wardeh: Host in the Machine - Towards Explainable AI framework which directs experiments to strengthen its ability to answer the question: “Where do viruses hide?”\n\nMost emerging viruses of significant consequence reach humans and domesticated animals via a broad spectrum of wild intermediate and reservoir hosts. However, we have currently only observed ~0.2% of all possible associations between known viruses and hosts, therefore, the vast majority of these potential virus/host associations remain unknown. Hence, our knowledge of host range, reservoirs, and ability to understand and mitigate high consequence viral outbreaks is severely limited.\n\n\n\nThis talk will showcase how the above problem can be expressed computationally, in ways that both preserve the intricacies of the interplay between the virus biology and host ecology. I will address the inherent biases in our knowledge of the natural world and how they affect our understanding of virus emergence and evolution.\n\n\n\nThrough multidisciplinary research encompassing computational biology, complex networks, machine learning, and experimental validation, this talk will highlight how we can advance our understanding of viral ecology and inform proactive strategies for disease surveillance and control.\n\nhttps://www.csc.liv.ac.uk/research/seminars/abstract.php?id=1232
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