Imagine being able to predict the reservoir species for a newly-found virus just from its genetic code. Using cutting edge machine learning techniques, that is precisely what researchers from the University of Glasgow’s Institute of Biodiversity, Animal Health & Comparative Medicine and the Centre for Virus Research have managed to do. Join us in this episode of Naturally Speaking as we speak with Simon Babayan and Daniel Streicker about their recent paper in Science.

The paper discussed in this podcast is: Babayan S, Orton R and Streicker DG. Predicting reservoir hosts and arthropod vectors from evolutionary signatures in RNA virus genomes. Science, 2018; 362 (6414): 577-580.

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This podcast was edited by Keila Meginnis and Taya Forde.

Feature image: Original artwork courtesy of PhD researcher Eleni Christoforou, 2019©

Intro and outro music sampled from: “The Curtain Rises” and “Early RiserKevin MacLeod [CC BY 3.0]

Posted by The Naturally Speaking Editors

A science pod-yssey and regular blog-yssey from the Institute of Biodiversity, Animal Health & Comparative Medicine at the University of Glasgow

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