Predicting zoonotic risk of influenza a viruses from host tropism protein signature using random forest

• Main Authors: Eng, C.L.P, Tong, J.C, Tan, T.W
• Other Authors: DEPT OF BIOCHEMISTRY
• Format: Article
• Published: 2020
• Subjects: amino acid sequence; area under the curve; Article; avian influenza; diagnostic test accuracy study; Influenza A virus; machine learning; nonhuman; physical chemistry; predictive value; random forest; receiver operating characteristic; retrospective study; sensitivity and specificity; viral tropism; zoonosis; animal; bird; epidemic; genetic database; genetics; host pathogen interaction; host range; human; influenza; orthomyxovirus infection; reproducibility; theoretical model; virology; viral protein; Animals; Area Under Curve; Birds; Databases, Genetic; Disease Outbreaks; Host Specificity; Host-Pathogen Interactions; Humans; Influenza in Birds; Influenza, Human; Machine Learning; Models, Theoretical; Orthomyxoviridae Infections; Reproducibility of Results; Retrospective Studies; Viral Proteins; Viral Tropism; Zoonoses
• Online Access: https://scholarbank.nus.edu.sg/handle/10635/176089
• Institution: National University of Singapore

10.3390/ijms18061135