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基于PCA的中药黄芩药效评价方法研究
引用本文:成巍,侯恩广,李珂,李树彬,赵渤年,于宗渊. 基于PCA的中药黄芩药效评价方法研究[J]. 山东科学, 2012, 25(1): 47-50. DOI: 10.3976/j.issn.1002-4026.2012.01.010
作者姓名:成巍  侯恩广  李珂  李树彬  赵渤年  于宗渊
作者单位:1.山东省汽车电子技术重点实验室,山东省科学院自动化研究所,山东 济南 250014;2.山东省中医药研究院,山东 济南 250014
基金项目:“十一五”国家科技支撑计划项目(2006BAI06A0203);山东省科学院博士基金项目(科基合字(2008)第25号)
摘    要:为实现基于谱效相关模式的中药黄芩的质量综合评价,采用主成分分析法(principal component analysis, PCA)对采集到的色谱指纹图谱和药效指标(抑菌率)的大量数据进行降维处理,然后建立中药黄芩谱效结合评价系统,测试结果证明了该方法的先进性与可靠性。文中的降维方法可以为中药材质量评价研究提供一种新的、可借鉴的思路和方法。

关 键 词:中药药效评价  谱效相关模式  主成分分析法  指纹图谱  黄芩  
收稿时间:2011-05-12

Research on principle component analysis based pharmacological effect  evaluation method for a kind of Chinese herbal medicine, Baikal skullcap root
CHENG Wei,HOU En-Guang,LI Ke,LI Shu-Bin,ZHAO Bo-Nian,XU Zong-Yuan. Research on principle component analysis based pharmacological effect  evaluation method for a kind of Chinese herbal medicine, Baikal skullcap root[J]. Shandong Science, 2012, 25(1): 47-50. DOI: 10.3976/j.issn.1002-4026.2012.01.010
Authors:CHENG Wei  HOU En-Guang  LI Ke  LI Shu-Bin  ZHAO Bo-Nian  XU Zong-Yuan
Affiliation:1.Shandong Provincial Key Laboratory of Automotive Electronic Technology, Institute of Automation, Shandong Academy of Sciences, Jinan 250014, China;2.Shandong Academy of Chinese Medicine, Jinan 250014, China
Abstract:We employ the algorithm of principal component analysis (PCA) to process the acquired chromatographic fingerprint and inhibitory rate by dimensionality reduction to realize chromatographic fingerprint and pharmacological effect correlation mode based comprehensive quality evaluation for Baikal skullcap root. Test results demonstrate its advances and higher reliability. This method provides us a new and referable idea for the quality evaluation of traditional Chinese herbal medicine.
Keywords:quality evaluation of traditional Chinese medicine  chromatographic fingerprint and pharmacological effect correlation mode  principal component analysis  fingerprint  Baikal skullcap root
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