ArticlePloS one2014
Identification and chronological analysis of genomic signatures in influenza A viruses.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Genetic diversification patterns in swine influenza A virus (H1N2) in vaccinated and nonvaccinated animals.Frontiers in cellular and infection microbiology · 2023Article
- Vaccination against swine influenza in pigs causes different drift evolutionary patterns upon swine influenza virus experimental infection and reduces the likelihood of genomic reassortments.Frontiers in cellular and infection microbiology · 2023Article
- Identifying host-specific amino acid signatures for influenza A viruses using an adjusted entropy measure.BMC bioinformatics · 2022Article
- Host-Adaptive Signatures of H3N2 Influenza Virus in Canine.Frontiers in veterinary science · 2021Article
- Comprehensive mapping of adaptation of the avian influenza polymerase protein PB2 to humans.eLife · 2019Article
- Identification of combinatorial host-specific signatures with a potential to affect host adaptation in influenza A H1N1 and H3N2 subtypes.BMC genomics · 2016Article
- Molecular analyses of H3N2 canine influenza viruses isolated from Korea during 2013-2014.Virus genes · 2016Article
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Authors and funding
4 authors.
Funding
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Abstract
An increase in the availability of data on the influenza A viruses (IAV) has enabled the identification of the potential determinants of IAV host specificity using computational approaches. In this study, we proposed an alternative approach, based on the adjusted Rand index (ARI), for the evaluation of genomic signatures of IAVs and their ability to distinguish hosts they infected. Our experiments showed that the host-specific signatures identified using the ARI were more characteristic of their hosts than those identified using previous measures. Our results provided updates on the host-specific genomic signatures in the internal proteins of the IAV based on the sequence data as of February 2013 in the National Center for Biotechnology Information (NCBI). Unlike other approaches for signature recognition, our approach considered not only the ability of signatures to distinguish hosts (according to the ARI), but also the chronological relationships among proteins. We identified novel signatures that could be mapped to known functional domains, and introduced a chronological analysis to investigate the changes in host-specific genomic signatures over time. Our chronological analytical approach provided results on the adaptive variability of signatures, which correlated with previous studies' findings, and indicated prospective adaptation trends that warrant further investigation.
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