PREDAC-FluB: predicting antigenic clusters of seasonal influenza B viruses with protein language model embedding based convolutional neural network.

ABSTRACT: Influenza poses a significant global public health threat, with vaccination being the most effective and economical preventive measure. However, these punctuated antigenic changes, particularly in HA, result in escape from the immunity that was induced by prior infection or vaccination. Accurately predicting antigenic variation and understanding the antigenic dynamics of influenza viruses are crucial for selecting appropriate vaccine strains, but no established methods exist for influenza B viruses. Therefore, we present PREDAC-FluB, a hybrid deep learning framework that integrates spatial feature extraction via CNN to model interactions in HA1 sequences, multimodal sequence representation combining ESM-2 embeddings with six physicochemical descriptors and continuous encoding (ESM2-7-featu

SUBMITTER: Xie W 

PROVIDER: S-EPMC12264208 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature