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HerDing: Herb recommendation system to treat diseases using genes and chemicals

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Abstract
In recent years, herbs have been researched for new drug candidates because they have a long empirical history of treating diseases and are relatively free from side effects. Studies to scientifically prove the medical efficacy of herbs for target diseases often spend a considerable amount of time and effort in choosing candidate herbs and in performing experiments to measure changes of marker genes when treating herbs. A computational approach to recommend herbs for treating diseasesmight be helpful to promote efficiency in the early stage of such studies. Although several databases related to traditional Chinese medicine have been already developed, there is no specialized Web tool yet recommending herbs to treat diseases based on disease-related genes. Therefore, we developed a novel search engine, HerDing, focused on retrieving candidate herb-related information with user search terms (a list of genes, a disease name, a chemical name or an herb name). HerDing was built by integrating public databases and by applying a textmining method. The HerDing website is free and open to all users, and there is no login requirement. © The Author(s) 2016.
Author(s)
Choi, WonjunChoi, Chan-HunKim, Young RanKim, Seon-JongNa, Chang-SuLee, Hyunju
Issued Date
2016-03
Type
Article
DOI
10.1093/database/baw011
URI
https://scholar.gist.ac.kr/handle/local/14303
Publisher
Oxford University Press
Citation
Database : the journal of biological databases and curation, v.2016
ISSN
1758-0463
Appears in Collections:
Department of AI Convergence > 1. Journal Articles
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