ArticleFrontiers in microbiology2025
Machine learning methods for predicting human-adaptive influenza A virus reassortment based on intersegment constraint.
Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Genomic similarity to quantitatively evaluate the reassortment potential of H7N9 with other subtypes of avian influenza viruses.Frontiers in cellular and infection microbiology · 2026Article
- Predicting host tropism in influenza a viruses: insights from multi-segment nucleotide signatures.Journal of translational medicine · 2025Article
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Authors and funding
6 authors.
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Abstract
Introduction: It is not clear about mechanisms underlining the inter-segment reassortment of Influenza A viruses (IAVs).We analyzed the viral nucleotide composition (NC) in coding sequences,examined the intersegment NC correlation, and predicted the IAV reassortment using machine learning (ML) approaches based on viral NC features. Methods: Unsupervised ML methods were used to examine the NC difference between human-adapted and zoonotic IAVs. Supervised ML models of random forest classifier (rfc) and multiple-layer preceptor (mlp) were developed to predict the human adaption to IAVs. Results: Our results demonstrated that the frequencies of thymine, cytosine, adenine,and guanine (t, c, a, and g), as well as the content of gc/at were consistently high or low for the segments of Discussion: In summary, there is a distinct human adaption-specific genomic NC between human IAVs and avian IAVs. The intersegment NC correlation constrains segment reassortment. This study presents a novel strategy for predicting IAV reassortment based on viral genetic compatibility.
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