Suhyun Ha, Sunyong Yoo, Moonshik Shin, J. Kwak, O. Kwon, M. Choi, K. Kang, Hojung Nam, Doheon Lee
{"title":"Integrative Database for Exploring Compound Combinations of Natural Products for Medical Effects","authors":"Suhyun Ha, Sunyong Yoo, Moonshik Shin, J. Kwak, O. Kwon, M. Choi, K. Kang, Hojung Nam, Doheon Lee","doi":"10.1145/2665970.2665986","DOIUrl":null,"url":null,"abstract":"Natural products used in dietary supplements, complementary and alternative medicine (CAM) and conventional medicine are composites of multiple chemical compounds. These chemical compounds potentially offer an extensive source for drug discovery with accumulated knowledge of efficacy and safety. However, existing natural product related databases have drawbacks in both standardization and structuralization of information. Therefore, in this work, we construct an integrated database of natural products by mapping the prescription, herb, compound, and phenotype information to international identifiers and structuralizing the efficacy information through database integration and text-mining methods. We expect that the constructed database could serve as a fundamental resource for the natural products research.","PeriodicalId":143937,"journal":{"name":"Data and Text Mining in Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data and Text Mining in Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2665970.2665986","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
Natural products used in dietary supplements, complementary and alternative medicine (CAM) and conventional medicine are composites of multiple chemical compounds. These chemical compounds potentially offer an extensive source for drug discovery with accumulated knowledge of efficacy and safety. However, existing natural product related databases have drawbacks in both standardization and structuralization of information. Therefore, in this work, we construct an integrated database of natural products by mapping the prescription, herb, compound, and phenotype information to international identifiers and structuralizing the efficacy information through database integration and text-mining methods. We expect that the constructed database could serve as a fundamental resource for the natural products research.