A sequence-based machine learning model for predicting antigenic distance for H3N2 influenza virus.

Interestingly, our predicted antigenic map aligns closely with the antigenic map generated with serological data. Thus, our method is a promising tool for detecting antigenic variants and guiding the selection of vaccine candidates.