Divide-and-conquer: machine-learning integrates mammalian and viral traits with network features to predict virus-mammal associations

Abstract

A more comprehensive map of viral host ranges can help identify and mitigate zoonotic and animal-disease risks. A divide-and-conquer approach which separates viral, mammalian and network features predicts over 20,000 unknown associations between known viruses and susceptible mammalian species.