ViPal: A framework for virulence prediction of influenza viruses with prior viral knowledge using genomic sequences.

ABSTRACT: Influenza viruses pose great threats to public health and cause enormous economic losses every year. Previous work has revealed the viral factors associated with the virulence of influenza viruses in mammals. However, taking prior viral knowledge represented by heterogeneous categorical and discrete information into account to explore virus virulence is scarce in the existing work. How to make full use of the preceding domain knowledge in virulence study is challenging but beneficial. This paper proposes a general framework named ViPal for virulence prediction in mice that incorporates discrete prior viral mutation and reassortment information based on all eight influenza segments. The posterior regularization technique is leveraged to transform prior viral knowledge into constraint featur

SUBMITTER: Yin R 

PROVIDER: S-EPMC10602211 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature