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首页> 外文期刊>BMC Systems Biology >Forecasting influenza A pandemic outbreak using protein dynamical network biomarkers
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Forecasting influenza A pandemic outbreak using protein dynamical network biomarkers

机译：使用蛋白质动态网络生物标记物预测甲型流感大流行爆发

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Background Influenza A virus is prone to mutation and susceptible to human beings and spread in the crowds when affected by the external environment or other factors. It is very necessary to forecast influenza A pandemic outbreak. Methods This paper studies the different states of influenza A in the method of dynamical network biomarkers. Through establishing protein dynamical network biomarkers of influenza A virus protein, a composite index is ultimately obtained to forecast influenza A pandemic outbreak. Results The composite index varies along with the state of pandemic influenza virus from a relatively steady state to critical state before outbreak and then to the outbreak state. When the composite index continuous decreases for 2 years and increases of more than o.1 suddenly, it means the next year is normally in the outbreak state. Therefore, we can predict and identify whether a certain year is in the critical state before influenza A outbreak or outbreak state by observing the variation of index value. Meanwhile, through data analysis for different countries influenza A pandemic outbreak in different countries can also be forecasted. Conclusions This indicates the composite index can provide significant warning information to detect the stage of influenza A, which will be significantly meaningful for the warning and prevention of influenza A pandemic.
机译：背景技术甲型流感病毒易受突变影响，易于感染人类，并在受到外部环境或其他因素影响时在人群中传播。预测甲型流感大流行暴发非常必要。方法采用动态网络生物标志物方法研究甲型流感的不同状态。通过建立甲型流感病毒蛋白质的蛋白质动态网络生物标记，最终获得了一个综合指数来预测甲型流感大流行的爆发。结果综合指数随大流行性流感病毒的状态而变化，从相对稳定的状态到爆发前的临界状态，再到爆发状态。当综合指数连续2年下降并突然超过o.1时，则表示第二年通常处于爆发状态。因此，通过观察指标值的变化，我们可以预测并确定某年处于甲型流感爆发之前的关键状态还是爆发状态。同时，通过对不同国家的数据分析，也可以预测不同国家的甲型流感大流行暴发。结论该综合指数可为检测甲型流感分期提供重要的预警信息，对预警和预防甲型流感大流行具有重要意义。

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