Dayan Wang

This paper develops FutureFlu, a framework to predict influenza vaccine strains by quantifying viral fitness, showing improved accuracy compared to current methods.

This paper introduces fluProfiler, a framework using viral sequences to predict antigenic relationships and improve vaccine strain selection by reducing reliance on time-consuming HI assays.

This paper introduces FluAdaX, a deep learning framework to predict influenza A virus cross-species transmission potential using genomic data, identifying key genes and variants associated with host adaptation.

This paper introduces FluRisk, a computational framework using genomic data and AI to assess the risk of emerging influenza viruses, showing improved performance over traditional methods.

This study models the antigenic evolution of seasonal influenza viruses using PREDAC and finds no need to update vaccine strains for the 2025 season.