Characterization and classification of adverse drug interactions.

Masataka Takarabe, Daichi Shigemizu, Masaaki Kotera, Susumu Goto, Minoru Kanehisa
{"title":"Characterization and classification of adverse drug interactions.","authors":"Masataka Takarabe,&nbsp;Daichi Shigemizu,&nbsp;Masaaki Kotera,&nbsp;Susumu Goto,&nbsp;Minoru Kanehisa","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Drug interactions which may cause harmful events are important for our health and new drag development. In the previous work, we extracted the drug interaction data from Japanese drug package inserts and generated the drug interaction network. The network contains a large number of drugs densely connected to each other, where drug targets and drug-metabolizing enzymes were shared in the drug interactions. In this study, we further analyzed the obtained drug interaction network by merging drugs into drug categories based on the Anatomical Therapeutic Chemical (ATC) classification. The merged data of drug interactions indicated drug properties that are related to drug interaction mechanisms or symptoms. We investigated the relationships between the drug groups and drug interaction mechanisms or symptoms.</p>","PeriodicalId":73143,"journal":{"name":"Genome informatics. International Conference on Genome Informatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genome informatics. International Conference on Genome Informatics","FirstCategoryId":"1085","ListUrlMain":"","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

Drug interactions which may cause harmful events are important for our health and new drag development. In the previous work, we extracted the drug interaction data from Japanese drug package inserts and generated the drug interaction network. The network contains a large number of drugs densely connected to each other, where drug targets and drug-metabolizing enzymes were shared in the drug interactions. In this study, we further analyzed the obtained drug interaction network by merging drugs into drug categories based on the Anatomical Therapeutic Chemical (ATC) classification. The merged data of drug interactions indicated drug properties that are related to drug interaction mechanisms or symptoms. We investigated the relationships between the drug groups and drug interaction mechanisms or symptoms.

分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
药物不良反应的特征和分类。
药物相互作用对我们的健康和新药开发具有重要的意义。在之前的工作中,我们从日本药品说明书中提取药物相互作用数据,并生成药物相互作用网络。该网络包含大量相互紧密连接的药物,其中药物靶点和药物代谢酶在药物相互作用中是共享的。在本研究中,我们进一步分析了获得的药物相互作用网络,将药物合并到基于解剖治疗化学(ATC)分类的药物类别中。药物相互作用的合并数据表明与药物相互作用机制或症状相关的药物特性。我们调查了药物组与药物相互作用机制或症状之间的关系。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Docking-calculation-based method for predicting protein-RNA interactions. Sign: large-scale gene network estimation environment for high performance computing. Linear regression models predicting strength of transcriptional activity of promoters. Database for crude drugs and Kampo medicine. Mechanism of cell cycle disruption by multiple p53 pulses.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1