ArticleFrontiers in genetics2021
A Codon-Pair Bias Associated With Network Interactions in Influenza A, B, and C Genomes.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- Multilayered nucleotide organization reveals purifying selection and host-driven adaptation in CPV and FPV.BMC veterinary research · 2026Article
- Mapping evolutionary paradigm of bovine viral diarrhea virusVirulence · 2025Article
- Mapping evolutionary paradigm of Oropouche virus driven by dinucleotide bias and context-dependent codon bias.Virulence · 2025Article
- Evolutionary paradigm of distinct viral coding regions of BVDV associated with different nucleotide usage patterns.BMC veterinary research · 2025Article
- Bias at the third nucleotide of codon pairs in virus and host genomes.Scientific reports · 2022Article
- Evolution and host adaptability of plant RNA viruses: Research insights on compositional biases.Computational and structural biotechnology journal · 2022Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A new codon-pair bias present in the genomes of different types of influenza virus is described. Codons with fewer network interactions are more frequency paired together than other codon-pairs in influenza A, B, and C genomes. A shared feature among three different influenza types suggests an evolutionary bias. Codon-pair preference can affect both speed of protein translation and RNA structure. This newly identified bias may provide insight into drivers of virus evolution.
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Registered trials
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