ArticleProceedings of the National Academy of Sciences of the United States of America2016
Prediction, dynamics, and visualization of antigenic phenotypes of seasonal influenza viruses.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 140 papers.
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140 citing papers in PubMed, 254 citations in OpenAlex.
- Safety and Immunogenicity of mRNA-1010, an Investigational Seasonal Influenza Vaccine, in Healthy Adults: Final Results From a Phase 1/2 Randomized Trial.The Journal of infectious diseases · 2025Trial
- Near real-time data on the human neutralizing antibody landscape to influenza virus in summer of 2026 shows antigenic advance of H3N2 subclade K region D mutants and H1N1 D.3.1.1 Sa mutants.bioRxiv : the preprint server for biology · 2026Article
- From sites to structure to serology: a roadmap for structure-aware molecular evolution of antigenically evolving viruses.Journal of virology · 2026Review
- Alignment-free prediction of cross-reactivity in influenza A (H3N2) anticipates antigenic drift.PLoS computational biology · 2026Article
- Article
- Predicting the antigenic evolution of seasonal influenza viruses using phylogenetic convergence.bioRxiv : the preprint server for biology · 2026Article
- A CNN-Based Model of Cross-Immunity to Influenza A(H3N2) Virus: Testing Under "Real-World" Conditions.Viruses · 2026Article
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- Near real-time data on the human neutralizing antibody landscape to influenza virus as of early 2026 to inform vaccine-strain selection.bioRxiv : the preprint server for biology · 2026Article
- Beyond alarmism: what Australia's influenza season really tells us about Italy.Pathogens and global health · 2026Article
- Near real-time data on the human neutralizing antibody landscape to influenza virus as of early 2026 to inform vaccine-strain selection.Virus evolution · 2026Article
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- High-throughput neutralization measurements correlate strongly with evolutionary success of human influenza strains.bioRxiv : the preprint server for biology · 2025Article
- Influenza vaccine effectiveness among primary and secondary school students in Shenzhen during the 2023/24 influenza season.Emerging microbes & infections · 2025Article
- Unraveling the mechanism behind the probable extinction of the B/Yamagata lineage of influenza B viruses.Nature communications · 2025Article
- Influenza vaccine strain selection with an AI-based evolutionary and antigenicity model.Nature medicine · 2025Article
- Different antigenic distance metrics generate similar predictions of influenza vaccine response breadth despite moderate correlation.PLoS computational biology · 2025Article
- Near real-time data on the human neutralizing antibody landscape to influenza virus to inform vaccine-strain selection in September 2025.bioRxiv : the preprint server for biology · 2025Article
- Assessing the structural boundaries of broadly reactive antibody interactions with diverse H3 influenza hemagglutinin proteins.Journal of virology · 2025Article
- PREDAC-FluB: predicting antigenic clusters of seasonal influenza B viruses with protein language model embedding based convolutional neural network.Briefings in bioinformatics · 2025Article
80 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors at 5 institutions in 3 countries.
Funding
Abstract
Human seasonal influenza viruses evolve rapidly, enabling the virus population to evade immunity and reinfect previously infected individuals. Antigenic properties are largely determined by the surface glycoprotein hemagglutinin (HA), and amino acid substitutions at exposed epitope sites in HA mediate loss of recognition by antibodies. Here, we show that antigenic differences measured through serological assay data are well described by a sum of antigenic changes along the path connecting viruses in a phylogenetic tree. This mapping onto the tree allows prediction of antigenicity from HA sequence data alone. The mapping can further be used to make predictions about the makeup of the future A(H3N2) seasonal influenza virus population, and we compare predictions between models with serological and sequence data. To make timely model output readily available, we developed a web browser-based application that visualizes antigenic data on a continuously updated phylogeny.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.