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首页> 外文期刊>PLoS Computational Biology >Predicting Meridian in Chinese traditional medicine using machine learning approaches
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Predicting Meridian in Chinese traditional medicine using machine learning approaches

机译:使用机器学习方法预测中医的经络

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摘要

In East Asia, plant-derived natural products, known as herb formulas, have been commonly used as Traditional Chinese Medicine (TCM) for disease prevention and treatment. According to the theory of TCM, herbs can be classified as different Meridians according to the balance of Yin and Yang, which are commonly understood as metaphysical concepts. Therefore, the scientific rational of Meridian classification remains poorly understood. The aim of our study was to provide a computational means to understand the classification of Meridians. We showed that the Meridians of herbs can be predicted by the molecular and chemical features of the ingredient compounds, suggesting that the Meridians indeed are associated with the properties of the compounds. Our work provided a novel chemoinformatics approach which may lead to a more systematic strategy to identify the mechanisms of action and active compounds for TCM herbs.
机译:在东亚,植物来源的天然产物,被称为草药配方,通常被用作中药(TCM),用于疾病的预防和治疗。根据中医理论,根据阴阳平衡,草药可以分为不同的经络,这通常被称为形而上学的概念。因此,对子午线分类的科学理性仍然知之甚少。我们研究的目的是提供一种了解子午线分类的计算方法。我们表明,可以通过成分化合物的分子和化学特征来预测草药的子午线,这表明子午线确实与化合物的特性有关。我们的工作提供了一种新颖的化学信息学方法,该方法可能导致更系统的策略来确定中药的作用机理和活性化合物。

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