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基于信息熵理论的黄酮类化合物分类。

Classification of flavonoid compounds by using entropy of information theory.

机构信息

Facultad de Ciencias Experimentales, Universidad Católica de, Valéncia San Vicente Mártir, Guillem de Castro-94, E-46001 Valencia, Spain.

出版信息

Phytochemistry. 2013 Sep;93:182-91. doi: 10.1016/j.phytochem.2013.03.024. Epub 2013 May 3.

Abstract

A total of 74 flavonoid compounds are classified into a periodic table by using an algorithm based on the entropy of information theory. Seven features in hierarchical order are used to classify structurally the flavonoids. From these features, the first three mark the group or column, while the last four are used to indicate the row or period in a table of periodic classification. Those flavonoids in the same group and period are suggested to show maximum similarity in properties. Furthermore, those with only the same group will present moderate similarity. In this report, the flavonoid compounds in the table, whose experimental data in bioactivity and antioxidant properties have been previously published, are related.

摘要

总共 74 种类黄酮化合物被一种基于信息论熵算法的方法进行分类,呈现在元素周期表中。利用 7 个层次特征对类黄酮结构进行分类。其中前 3 个特征标志着族或列,而最后 4 个特征则用于指示表中的行或周期。在同一族和周期中的类黄酮化合物被认为在性质上具有最大的相似性。此外,那些只有相同族的化合物也会表现出中等程度的相似性。在本报告中,将相关联的表中类黄酮化合物与之前已经发表的生物活性和抗氧化性质的实验数据联系起来。

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