ArticleGenome research2008
Networks of genomic co-occurrence capture characteristics of human influenza A (H3N2) evolution.
Article in Genome research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 52 citations in OpenAlex.
- Molecular evolution and spatial transmission of severe fever with thrombocytopenia syndrome virus.Nature communications · 2026Article
- Co-Mutations and Possible Variation Tendency of the Spike RBD and Membrane Protein in SARS-CoV-2 by Machine Learning.International journal of molecular sciences · 2024Article
- Understanding the host-pathogen evolutionary balance through Gaussian process modeling of SARS-CoV-2.Patterns (New York, N.Y.) · 2023Article
- SARS2Mutant: SARS-CoV-2 amino-acid mutation atlas database.NAR genomics and bioinformatics · 2023Article
- Dominant clade-featured SARS-CoV-2 co-occurring mutations reveal plausible epistasis: An in silico based hypothetical model.Journal of medical virology · 2022Article
- Nucleotide-based genetic networks: Methods and applications.Journal of biosciences · 2022Article
- Comprehensive analysis of genomic diversity of SARS-CoV-2 in different geographic regions of India: an endeavour to classify Indian SARS-CoV-2 strains on the basis of co-existing mutations.Archives of virology · 2021Article
- Analysis of human mitochondrial genome co-occurrence networks of Asian population at varying altitudes.Scientific reports · 2021Article
- Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review.Journal of medical Internet research · 2020Article
- Codon based co-occurrence network motifs in human mitochondria.Scientific reports · 2018Article
- Rules of co-occurring mutations characterize the antigenic evolution of human influenza A/H3N2, A/H1N1 and B viruses.BMC medical genomics · 2016Article
- Predicting the Mutating Distribution at Antigenic Sites of the Influenza Virus.Scientific reports · 2016Article
- Network of co-mutations in Ebola virus genome predicts the disease lethality.Cell research · 2015Article
- Monitoring infectious diseases in the big data era.Science bulletin · 2015Article
- Computational prediction of vaccine strains for human influenza A (H3N2) viruses.Journal of virology · 2014Article
- Free-energy simulations reveal that both hydrophobic and polar interactions are important for influenza hemagglutinin antibody binding.Biophysical journal · 2012Article
- Mapping of H3N2 influenza antigenic evolution in China reveals a strategy for vaccine strain recommendation.Nature communications · 2012Article
- Inference of genotype-phenotype relationships in the antigenic evolution of human influenza A (H3N2) viruses.PLoS computational biology · 2012Article
- Identification of novel conserved functional motifs across most Influenza A viral strains.Virology journal · 2011Article
- Allele dynamics plots for the study of evolutionary dynamics in viral populations.Nucleic acids research · 2011Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The recent availability of full genomic sequence data for a large number of human influenza A (H3N2) virus isolates over many years provides us an opportunity to analyze human influenza virus evolution by considering all gene segments simultaneously. However, such analysis requires development of new computational models that can capture the complex evolutionary features over the entire genome. By analyzing nucleotide co-occurrence over the entire genome of human H3N2 viruses, we have developed a network model to describe H3N2 virus evolutionary patterns and dynamics. The network model effectively captures the evolutionary antigenic features of H3N2 virus at the whole-genome level and accurately describes the complex evolutionary patterns between individual gene segments. Our analyses show that the co-occurring nucleotide modules apparently underpin the dynamics of human H3N2 evolution and that amino acid substitutions corresponding to nucleotide co-changes cluster preferentially in known antigenic regions of the viral HA. Therefore, our study demonstrates that nucleotide co-occurrence networks represent a powerful method for tracking influenza A virus evolution and that cooperative genomic interaction is a major force underlying influenza virus evolution.
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