Exploring the Same Syndrome Existing in RA and DM through Data Mining

Guo Hongtao , Zheng Guang , He Xiaojuan , Zhang Chi , Lu Cheng , Zha Qinglin , Jiang Miao , Lu Aiping
{"title":"Exploring the Same Syndrome Existing in RA and DM through Data Mining","authors":"Guo Hongtao ,&nbsp;Zheng Guang ,&nbsp;He Xiaojuan ,&nbsp;Zhang Chi ,&nbsp;Lu Cheng ,&nbsp;Zha Qinglin ,&nbsp;Jiang Miao ,&nbsp;Lu Aiping","doi":"10.1016/S1876-3553(11)60029-X","DOIUrl":null,"url":null,"abstract":"<div><p>It is meaningful to search for the same syndromes existing among different diseases. One important terminology in Chinese medicine is called treating different diseases with the same therapy. In the clinical practice of Chinese medicine, some patients with rheumatoid arthritis and some other patients with diabetes mellitus can be treated with similar therapies. This suggests that there should be something commonly existing in the literature of different diseases unrevealed, i.e., biological networks. It is possible to mine those similar biological networks out. In this paper, we propose an algorithm to retrieve simple and meaningful networks from large data sets of rheumatoid arthritis and diabetes mellitus. We transfer XML type data sets to the structured database of Microsoft® SQL® and visualize them into different graphs by software Cytoscape. The results suggest that Huangqi (Radix Astragali), Guizhi (Ramulus Cinnamomi), Shaoyao (Radix Paeonise Alba), Zhimu (Rhizoma Anemarrhenae), Danggui (Radix Angelicae Sinensis), Chuanxiong (Rhizoma Chuanxiong), Maidong (Tuber Ophiopogonis), Shaoyao (Radix Dioscoreae), and Xuanshen (Radix Scrophulariae) are the commonly used herbal medicines. Huangqi (Radix Astragali) and Danggui (Radix Angelicae Sinensis) are of the core association. Quickening the blood and transforming stasis is the treatment principles for some pattern of rheumatoid arthritis and diabetes mellitus. The network visualized in these figures shows that those pairs of herbs in the two diseases are associated with the central commonly-existing biological networks.</p></div>","PeriodicalId":101287,"journal":{"name":"World Science and Technology","volume":"12 5","pages":"Pages 818-822"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1876-3553(11)60029-X","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S187635531160029X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

It is meaningful to search for the same syndromes existing among different diseases. One important terminology in Chinese medicine is called treating different diseases with the same therapy. In the clinical practice of Chinese medicine, some patients with rheumatoid arthritis and some other patients with diabetes mellitus can be treated with similar therapies. This suggests that there should be something commonly existing in the literature of different diseases unrevealed, i.e., biological networks. It is possible to mine those similar biological networks out. In this paper, we propose an algorithm to retrieve simple and meaningful networks from large data sets of rheumatoid arthritis and diabetes mellitus. We transfer XML type data sets to the structured database of Microsoft® SQL® and visualize them into different graphs by software Cytoscape. The results suggest that Huangqi (Radix Astragali), Guizhi (Ramulus Cinnamomi), Shaoyao (Radix Paeonise Alba), Zhimu (Rhizoma Anemarrhenae), Danggui (Radix Angelicae Sinensis), Chuanxiong (Rhizoma Chuanxiong), Maidong (Tuber Ophiopogonis), Shaoyao (Radix Dioscoreae), and Xuanshen (Radix Scrophulariae) are the commonly used herbal medicines. Huangqi (Radix Astragali) and Danggui (Radix Angelicae Sinensis) are of the core association. Quickening the blood and transforming stasis is the treatment principles for some pattern of rheumatoid arthritis and diabetes mellitus. The network visualized in these figures shows that those pairs of herbs in the two diseases are associated with the central commonly-existing biological networks.

通过数据挖掘探索类风湿关节炎和糖尿病的同证
寻找不同疾病间存在的相同证候具有重要意义。中医有一个重要的术语叫“同一疗法治疗不同疾病”。在中医临床实践中,部分类风湿关节炎患者和部分糖尿病患者可以采用类似的治疗方法。这表明,在不同疾病的文献中应该有一些共同存在的东西未被揭示,即生物网络。挖掘出这些相似的生物网络是可能的。在本文中,我们提出了一种从类风湿性关节炎和糖尿病的大型数据集中检索简单而有意义的网络的算法。我们将XML类型的数据集传输到Microsoft®SQL®结构化数据库中,并通过Cytoscape软件将它们可视化成不同的图形。结果表明,黄芪、桂枝、芍药、知母、当归、川芎、麦冬、芍药、玄参是常用的中草药。黄芪(黄芪)和当归(当归)是核心结合体。活血化瘀是类风湿关节炎和糖尿病某些证型的治疗原则。在这些图中可视化的网络表明,这两种疾病的草药对与中心普遍存在的生物网络有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信