Veterinary ScienceNature Communications
Divide-and-conquer: machine-learning integrates mammalian and viral traits with network features to predict virus-mammal associations
M. Wardeh, M. S. C. Blagrove, et al.
This groundbreaking study conducted by Maya Wardeh, Marcus S. C. Blagrove, Kieran J. Sharkey, and Matthew Baylis reveals the potential of machine learning in uncovering over 20,000 unknown virus-mammal associations, highlighting a significant gap in our understanding of these relationships, especially among wild mammals and various viruses.
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