PREDAC-CNN: predicting antigenic clusters of seasonal influenza A viruses with convolutional neural network.

ABSTRACT: Vaccination stands as the most effective and economical strategy for prevention and control of influenza. The primary target of neutralizing antibodies is the surface antigen hemagglutinin (HA). However, ongoing mutations in the HA sequence result in antigenic drift. The success of a vaccine is contingent on its antigenic congruence with circulating strains. Thus, predicting antigenic variants and deducing antigenic clusters of influenza viruses are pivotal for recommendation of vaccine strains. The antigenicity of influenza A viruses is determined by the interplay of amino acids in the HA1 sequence. In this study, we exploit the ability of convolutional neural networks (CNNs) to extract spatial feature representations in the convolutional layers, which can discern interactions between ami

SUBMITTER: Meng J 

PROVIDER: S-EPMC10859661 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature