Influenza virus genotype to phenotype predictions through machine learning: a systematic review
Author:
Affiliation:
1. Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA, USA
2. Department of Computer Science, School of Engineering, Tufts University, Medford, MA, USA
Funder
Animal and Plant Health Inspection Service
National Institute of Allergy and Infectious Diseases
Publisher
Informa UK Limited
Subject
Virology,Infectious Diseases,Drug Discovery,General Medicine,Immunology,Microbiology,Parasitology,Epidemiology
Link
https://www.tandfonline.com/doi/pdf/10.1080/22221751.2021.1978824
Reference68 articles.
1. A guide to machine learning for bacterial host attribution using genome sequence data
2. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
3. The Influenza Virus Resource at the National Center for Biotechnology Information
4. Influenza Research Database: An integrated bioinformatics resource for influenza virus research
5. GISAID: Global initiative on sharing all influenza data – from vision to reality
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