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  Prediction, dynamics, and visualization of antigenic phenotypes of seasonal influenza viruses

Neher, R., Bedford, T., Daniels, R., Russell, C., & Shraiman, B. (2016). Prediction, dynamics, and visualization of antigenic phenotypes of seasonal influenza viruses. Proceedings of the National Academy of Sciences of the United States of America, 113(12), E1701-E1709. doi:10.1073/pnas.1525578113.

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 Creators:
Neher, RA1, Author           
Bedford, T, Author
Daniels, RS, Author
Russell, CA, Author
Shraiman, BI, Author
Affiliations:
1Research Group Evolutionary Dynamics and Biophysics, Max Planck Institute for Developmental Biology, Max Planck Society, ou_3377926              

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 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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 Dates: 2016-03
 Publication Status: Issued
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Title: Proceedings of the National Academy of Sciences of the United States of America
  Other : PNAS
  Other : Proceedings of the National Academy of Sciences of the USA
  Abbreviation : Proc. Natl. Acad. Sci. U. S. A.
Source Genre: Journal
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Publ. Info: Washington, D.C. : National Academy of Sciences
Pages: - Volume / Issue: 113 (12) Sequence Number: - Start / End Page: E1701 - E1709 Identifier: ISSN: 0027-8424
CoNE: https://pure.mpg.de/cone/journals/resource/954925427230