ArticleBMC medical genomics2020
HopPER: an adaptive model for probability estimation of influenza reassortment through host prediction.
Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Influenza virus genotype to phenotype predictions through machine learning: a systematic review.Emerging microbes & infections · 2021Pooled it
- Fast and accurate identification of emerging viral reassortment from genome sequences.Nucleic acids research · 2026Article
- Deep learning predicts potential reassortments of avian H5N1 with human influenza viruses.National science review · 2025Article
- Influenza virus reassortment patterns exhibit preference and continuity while uncovering cross-species transmission events.Briefings in bioinformatics · 2025Article
- WaveSeekerNet: accurate prediction of influenza A virus subtypes and host source using attention-based deep learning.GigaScience · 2025Article
- Visualizing and deciphering influenza A(H1N1) pdm09 reassortment in the 2019-23 seasons.Virus evolution · 2025Article
- ViPal: A framework for virulence prediction of influenza viruses with prior viral knowledge using genomic sequences.Journal of biomedical informatics · 2023Article
- Exploring the Lethality of Human-Adapted Coronavirus Through Alignment-Free Machine Learning Approaches Using Genomic Sequences.Current genomics · 2021Article
- Progress and Challenge in Computational Identification of Influenza Virus Reassortment.Virologica Sinica · 2021Review
- Avian Influenza in Wild Birds and Poultry: Dissemination Pathways, Monitoring Methods, and Virus Ecology.Pathogens (Basel, Switzerland) · 2021Review
- Using Spheroids as Building Blocks Towards 3D Bioprinting of Tumor Microenvironment.International journal of bioprinting · 2021Review
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4 authors.
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Abstract
backgroundInfluenza reassortment, a mechanism where influenza viruses exchange their RNA segments by co-infecting a single cell, has been implicated in several major pandemics since 19th century. Owing to the significant impact on public health and social stability, great attention has been received on the identification of influenza reassortment.
methodsWe proposed a novel computational method named HopPER (Host-prediction-based Probability Estimation of Reassortment), that sturdily estimates reassortment probabilities through host tropism prediction using 147 new features generated from seven physicochemical properties of amino acids. We conducted the experiments on a range of real and synthetic datasets and compared HopPER with several state-of-the-art methods.
resultsIt is shown that 280 out of 318 candidate reassortants have been successfully identified. Additionally, not only can HopPER be applied to complete genomes but its effectiveness on incomplete genomes is also demonstrated. The analysis of evolutionary success of avian, human and swine viruses generated through reassortment across different years using HopPER further revealed the reassortment history of the influenza viruses.
conclusionsOur study presents a novel method for the prediction of influenza reassortment. We hope this method could facilitate rapid reassortment detection and provide novel insights into the evolutionary patterns of influenza viruses.
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