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Characterization of the heterogeneity in SARS-CoV-2 fitness dynamics via graph representation learning.

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Title: Characterization of the heterogeneity in SARS-CoV-2 fitness dynamics via graph representation learning.
Authors: Wang, Zengmiao1 (AUTHOR) wangzengmiao@gmail.com, Zhou, Ziqin1 (AUTHOR), Wang, Junfu2 (AUTHOR), Yang, Lingyue1 (AUTHOR), Zhang, Zhirui3 (AUTHOR), Xu, Weina2 (AUTHOR), Liu, Zeming2 (AUTHOR), Ge, Yuxi1 (AUTHOR), Yang, Liang4 (AUTHOR), Wang, Xiaoli5,6,7 (AUTHOR), Yang, Peng5,6,7 (AUTHOR), Wang, Quanyi5,6,7 (AUTHOR), Cao, Yunlong8,9,10 (AUTHOR) yunlongcao@pku.edu.cn, Guo, Yuanfang2 (AUTHOR) andyguo@buaa.edu.cn, Tian, Huaiyu1,11 (AUTHOR) tianhuaiyu@gmail.com
Source: PLoS Computational Biology. 1/12/2026, Vol. 22 Issue 1, p1-23. 23p.
Database: Academic Search Ultimate
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  Data: Characterization of the heterogeneity in SARS-CoV-2 fitness dynamics via graph representation learning.
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  Data: <searchLink fieldCode="JN" term="%22PLoS+Computational+Biology%22">PLoS Computational Biology</searchLink>. 1/12/2026, Vol. 22 Issue 1, p1-23. 23p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=190826400
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              Text: 1/12/2026
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