Divide-and-conquer: machine-learning integrates mammalian and viral traits with network features to predict virus-mammal associations.
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| Title: | Divide-and-conquer: machine-learning integrates mammalian and viral traits with network features to predict virus-mammal associations. |
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| Authors: | Wardeh M; Department of Livestock and One Health, Institute of Infection, Veterinary & Ecological Sciences, University of Liverpool, Liverpool, UK. maya.wardeh@liverpool.ac.uk.; Department of Mathematical Sciences, University of Liverpool, Liverpool, UK. maya.wardeh@liverpool.ac.uk., Blagrove MSC; Department of Evolution, Ecology and Behaviour, Institute of Infection, Veterinary & Ecological Sciences, University of Liverpool, Liverpool, UK., Sharkey KJ; Department of Mathematical Sciences, University of Liverpool, Liverpool, UK., Baylis M; Department of Livestock and One Health, Institute of Infection, Veterinary & Ecological Sciences, University of Liverpool, Liverpool, UK.; Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK. |
| Source: | Nature communications [Nat Commun] 2021 Jun 25; Vol. 12 (1), pp. 3954. Date of Electronic Publication: 2021 Jun 25. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2041-1723 |
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| DOI: | 10.1038/s41467-021-24085-w |
