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Predicting Antigenicity of Influenza A Viruses Using biophysical ideas

机译:使用生物物理思想预测流感病毒的抗原性

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Antigenic variations of influenza A viruses are induced by genomic mutation in their trans-membrane protein HA1, eliciting viral escape from neutralization by antibodies generated in prior infections or vaccinations. Prediction of antigenic relationships among influenza viruses is useful for designing (or updating the existing) influenza vaccines, provides important insights into the evolutionary mechanisms underpinning viral antigenic variations, and helps to understand viral epidemiology. In this study, we present a simple and physically interpretable model that can predict antigenic relationships among influenza A viruses, based on biophysical ideas, using both genomic amino acid sequences and experimental antigenic data. We demonstrate the applicability of the model using a benchmark dataset of four subtypes of influenza A (H1N1, H3N2, H5N1, and H9N2) viruses and report on its performance profiles. Additionally, analysis of the model's parameters confirms several observations that are consistent with the findings of other previous studies, for which we provide plausible explanations.
机译:流感的抗原变化是通过基因组突变在其跨膜蛋白HA1中引起的抗原变异,引起病毒逃逸通过现有感染或疫苗接种中产生的抗体中和。流感病毒之间的抗原关系预测可用于设计(或更新现有的)流感疫苗,为缺乏病毒抗原变异的进化机制提供了重要的见解,并有助于理解病毒流行病学。在这项研究中,我们介绍了一种简单且物理上可解释的模型,可以使用基因组氨基酸序列和实验抗原数据来预测流感病毒的抗原关系。我们使用甲型(H1N1,H3N2,H5N1和H9N2)病毒的四种亚型的基准数据集来证明模型的适用性,并报告其性能型材。此外,模型参数的分析确认了几种与其他先前研究的结果一致的观察结果,我们提供了合理的解释。

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