Divide-and-conquer: machine-learning integrates mammalian and | ResearchBunny

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Abstract

This study addresses the limited knowledge of viral host ranges by applying a machine-learning approach to predict unknown virus-mammal associations. The researchers used a "divide-and-conquer" strategy, separating viral, mammalian, and network features into three perspectives, each independently predicting associations. The approach predicted over 20,000 unknown associations, suggesting a significant underestimation of current knowledge, particularly for wild mammals and viruses like lyssaviruses, bornaviruses, and rotaviruses.

Publisher

Nature Communications

Published On

Jun 25, 2021

Authors

Maya Wardeh, Marcus S. C. Blagrove, Kieran J. Sharkey, Matthew Baylis

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