Journal of
Medicinal Plants Research

  • Abbreviation: J. Med. Plants Res.
  • Language: English
  • ISSN: 1996-0875
  • DOI: 10.5897/JMPR
  • Start Year: 2007
  • Published Articles: 3834

Full Length Research Paper

Research on herbal combinations of traditional Chinese medicine for chronic gastritis based on network biology

Peng Lu1#, Qingqiong Deng2#, Chenghe Shi3#, Yibao Gao1, Jianqiang Yi1, Mingquan Zhou2, Yiping Yang1 and Yuhao Zhao4*
1Institute of Automation, Chinese Academy of Sciences, Beijing 100190, P. R. China. 2College of Information Science and Technology, Beijing Normal University, No. 19 Xin-Jie-Kou-Wai Street, Beijing 100875, China. 3Department of Traditional Chinese Medicine, Peking University Third Hospital, Beijing 100191, P. R. China. 4School of Traditional Chinese, Medicine, Capital Medical University, 100069, Beijing, P. R. China.
Email: [email protected]

  •  Accepted: 19 December 2011
  •  Published: 09 February 2012

Abstract

Herbal combinations are important for traditional Chinese medicine physicians to treat diseases. Based on Professor GAO Zhongying’s medical records, combination laws are explored in order to study and inherit Professor GAO’s academic thoughts and improve the level of clinical treatment from multiple perspectives in treating chronic gastritis. Based on an entropy clustering method of complex systems, Professor GAO’s formula data is mined to draw the combinations which have good effects on the treatment of chronic gastritis. Meanwhile, the software Pajek developed for complex network was applied in the process. It not only provides a group of fast and efficient algorithms for to analyze complex networks, but also presents a visual interface to facilitate the understanding on the structural characteristics of complex networks from a visual point of view. Through analyzing the commonness of Professor GAO’s formulas, we found the compatibility structure that reflected formula thinking and core clinical features supported the arrangement of Professor GAO’s experiences. Through the procedure mentioned earlier, we analyzed and screened 730 formulas in the database and found 30 herbs most frequently used in the treatment of chronic gastritis. By applying the measure of modified mutual information, we got 94 commonly-used herbs with correlation coefficients above 0.05 and through the entropy clustering method of complex systems, we found 11 core combinations. The entropy clustering method of complex systems was used to build the association among 80 herbs commonly used to treat chronic gastritis, and then 122 associations were obtained. We draw out the complex network graph of herbs commonly used for chronic gastritis.These results are completely in line with clinical practices, and they are essentially the commonly used herbs employed by Professor GAO Zhongying for chronic gastritis.

 

Key words: Herbal combination, chronic gastritis, entropy clustering of complex systems, complex network.