贝叶斯网络模型在中药整体药性特征分析中的应用

山东大学学报(医学版) ›› 2011, Vol. 49 ›› Issue (5): 147-152.

贝叶斯网络模型在中药整体药性特征分析中的应用

齐方1，容蓉2，薛付忠1

1.山东大学公共卫生学院流行病与卫生统计学研究所，济南 250012； 2.山东中医药大学药学院，济南 250355

收稿日期:2011-03-22 出版日期:2011-05-10 发布日期:2011-05-10
通讯作者: 薛付忠(1964- ），男，副教授，博士生导师，主要从事中药药性统计分析方法研究。E-mail：xuefzh@sdu.edu.cn
作者简介:齐方(1986- )，女，硕士研究生，主要从事中药药性识别的统计模型研究。
基金资助:
国家重点基础研究发展计划(973计划)课题（2007CB512600）：中药药性理论相关基础问题研究（2007CB512601）。

Application of the Bayesian network in Chinese herbal medicine property recognition

QI Fang1， RONG Rong2， XUE Fu-zhong1

1. Institute of Epidemiology and Health Statistics, School of Public Health, Shandong University, Jinan 250012, China;
2. School of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China

Received:2011-03-22 Online:2011-05-10 Published:2011-05-10

摘要/Abstract

摘要：

目的阐明物质成分与中药药性间的内在联系和定量关系，选择药性特征标记，建立物质成分与中药整体药性间的贝叶斯网络模型，以期利用网络推理和复原中药整体药性。方法以还原论研究为基础，遵循中药基础理论的系统论原理，基于高效液相色谱技术，将偏最小二乘判别分析与贝叶斯网络模型有机结合，构建物质成分之间“君、臣、佐、使”的网络结构。结果以偏最小二乘判别模型选择出的37个药性特征标记作为节点所构建的中药整体药性贝叶斯网络模型，灵敏度、特异度高（ROC曲线下面积达0.98）；对中药药性判别能力强，训练集判别正确率达93.88%，对测试集的预测率达100%。结论中药整体药性贝叶斯网络具有明显的模块化结构，适宜解释中药药性特征标记之间的组合关系并能复原中药整体药性。

关键词: 贝叶斯网络；中药药性；高效液相色谱

Abstract:

Objective To clarify internal relation and quality relationship between the material composition and the Chinese herbal medicine property (CHMP), to establish the Bayesian network model among ‘composition’ and ‘CHMP’， and to infer and restore the CHMP by means of network. Methods According to the reductionism mode, high-performance liquid chromatography (HPLC) technology was combined with the Partial Least Squares Discriminant Analysis (PLS-DA) to identify the CHMPmarkers. Then based on the system theory, the Bayesian network model of CHMP-markers and CHMP was structured. Results 37 CHMP-markers were selected by the PLS-DA model to build the Bayesian network. It had high sensitivity, specificity (AUC=0.98) and discriminative power. Using this network to recognize the CHMP, the discriminative accuracy of the training set was 93.88% and the predictive accuracy of the testing set was 100%. Conclusion The Bayesian network has apparent modular construction， and it could explain the compatibility and pathways among the composition and the CHMP.

Key words: Bayesian network； Chinese herbal medicine property； High-performance liquid chromatography

中图分类号:

R282.5

齐方1，容蓉2，薛付忠1. 贝叶斯网络模型在中药整体药性特征分析中的应用[J]. 山东大学学报(医学版), 2011, 49(5): 147-152.

QI Fang1， RONG Rong2， XUE Fu-zhong1. Application of the Bayesian network in Chinese herbal medicine property recognition[J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2011, 49(5): 147-152.

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