ArticleMethods in molecular biology (Clifton, N.J.)2025
Concepts and Methods for Predicting Viral Evolution.
Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Predicting genetic evolution of viruses to identify suitable vaccines using artificial intelligence.Scientific reports · 2026Article
- Stochastic intracellular replication dynamics shape population-level evolution in Influenza A Virus.Virus evolution · 2026Article
- Artificial intelligence for coordinating vaccine design, antiviral discovery, and real-world monitoring in the era of emerging and endemic viral threats.Frontiers in pharmacology · 2026Review
- Article
- Influenza vaccine strain selection with an AI-based evolutionary and antigenicity model.Nature medicine · 2025Article
- T cell epitope mapping reveals immunodominance of evolutionarily conserved regions within SARS-CoV-2 proteome.iScience · 2025Article
- Epitope-Specific Antibody Immunodominance Driving Antibody and Influenza Viral Evolution During 2010- 2024.Open forum infectious diseases · 2025Article
- Measures of Population Immunity Can Predict the Dominant Clade of Influenza A (H3N2) in the 2017-2018 Season and Reveal Age-Associated Differences in Susceptibility and Antibody-Binding Specificity.Influenza and other respiratory viruses · 2024Article
- Measures of population immunity can predict the dominant clade of influenza A (H3N2) in the 2017-2018 season and reveal age-associated differences in susceptibility and antibody-binding specificity.medRxiv : the preprint server for health sciences · 2024Article
- Monitoring of Immune Memory by Phenotypical Lymphocyte Subsets Identikit: An Observational Study in a Blood Donors' Cohort.Journal of personalized medicine · 2024Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein hemagglutinin targeted by human antibodies. Here, we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to 1 year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available at https://previr.app .
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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.