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This content will become publicly available on February 18, 2021

Title: Early prediction of antigenic transitions for influenza A/H3N2

Authors:
ORCiD logo [1];  [2];  [3]
  1. Los Alamos National Laboratory
  2. Fred Hutchinson Cancer Research Center (United States)
  3. University of Texas at Austin
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
work performed elsewhere
OSTI Identifier:
1604006
Report Number(s):
[LA-UR-19-29731]
[Journal ID: 1553-7358 (Electronic)]
Grant/Contract Number:  
[89233218CNA000001]
Resource Type:
Accepted Manuscript
Journal Name:
PLoS Computational Biology (Online)
Additional Journal Information:
[Journal Name: PLoS Computational Biology (Online); Journal Volume: 16; Journal Issue: 2]
Country of Publication:
United States
Language:
English
Subject:
Biological Science; Computer Science

Citation Formats

Castro, Lauren Ann, Bedford, Trevor, and Ancel Meyers, Lauren. Early prediction of antigenic transitions for influenza A/H3N2. United States: N. p., 2020. Web. doi:10.1371/journal.pcbi.1007683.
Castro, Lauren Ann, Bedford, Trevor, & Ancel Meyers, Lauren. Early prediction of antigenic transitions for influenza A/H3N2. United States. doi:10.1371/journal.pcbi.1007683.
Castro, Lauren Ann, Bedford, Trevor, and Ancel Meyers, Lauren. Tue . "Early prediction of antigenic transitions for influenza A/H3N2". United States. doi:10.1371/journal.pcbi.1007683.
@article{osti_1604006,
title = {Early prediction of antigenic transitions for influenza A/H3N2},
author = {Castro, Lauren Ann and Bedford, Trevor and Ancel Meyers, Lauren},
abstractNote = {},
doi = {10.1371/journal.pcbi.1007683},
journal = {PLoS Computational Biology (Online)},
number = [2],
volume = [16],
place = {United States},
year = {2020},
month = {2}
}

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