Using amino acid features to identify the pathogenicity of influenza B virus.

ABSTRACT:

Background

Influenza B virus can cause epidemics with high pathogenicity, so it poses a serious threat to public health. A feature representation algorithm is proposed in this paper to identify the pathogenicity phenotype of influenza B virus.

Methods

The dataset included all 11 influenza virus proteins encoded in eight genome segments of 1724 strains. Two types of features were hierarchically used to build the prediction model. Amino acid features were directly delivered from 67 feature descriptors and input into the random forest classifier to output informative features about the class label and probabilistic prediction. The sequential forward search strategy was used to optimize the informative features. The final features for each strain had low dimensions and included

SUBMITTER: Kou Z 

PROVIDER: S-EPMC9066401 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature