%0 Journal Article
%A Cirac, Ana
%A Poirey, Remy
%A Dieckmeyer, Michael
%A Witter, Klaus
%A Delecluse, Henri-Jacques
%A Behrends, Uta
%A Mautner, Josef
%T Immunoinformatic Analysis Reveals Antigenic Heterogeneity of Epstein-Barr Virus Is Immune-Driven.
%J Frontiers in immunology
%V 12
%@ 1664-3224
%C Lausanne
%I Frontiers Media
%M DKFZ-2022-00025
%P 796379
%D 2021
%Z #EA:F100#
%X Whole genome sequencing of Epstein-Barr virus (EBV) isolates from around the world has uncovered pervasive strain heterogeneity, but the forces driving strain diversification and the impact on immune recognition remained largely unknown. Using a data mining approach, we analyzed more than 300 T-cell epitopes in 168 published EBV strains. Polymorphisms were detected in approximately 65
%K Epstein-Barr virus (Other)
%K T-cell epitope (Other)
%K immunoinformatics (Other)
%K strain variants (Other)
%K virus evolution (Other)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:34975903
%2 pmc:PMC8716887
%R 10.3389/fimmu.2021.796379
%U https://inrepo02.dkfz.de/record/178375