Computational predicting the human infectivity of H7N9 influenza viruses isolated from avian hosts.

ABSTRACT: The genome composition of a given avian influenza virus is the primary determinant of its potential for cross-species transmission from birds to humans. Here, we introduce a viral genome-based computational tool that can be used to evaluate the human infectivity of avian isolates of influenza A H7N9 viruses, which can enable prediction of the potential risk of these isolates infecting humans. This tool, which is based on a novel class weight-biased logistic regression (CWBLR) algorithm, uses the sequences of the eight genome segments of an H7N9 strain as the input and gives the probability of this strain infecting humans (reflecting its human infectivity). We examined the replication efficiency and the pathogenicity of several H7N9 avian isolates that were predicted to have very low or hig

SUBMITTER: Sun Y 

PROVIDER: S-EPMC8246913 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature