Wonjun Choi, Chan-Hun Choi, Young Ran Kim, Seon-Jong Kim, Chang-Su Na and Hyunju Lee. HerDing: herb recommendation system to treat diseases using genes and chemicals. Database (Oxford), 2016 March 15; 2016:baw011 (IF: 3.372) (JCR: 7/57, 12.3%, MATHEMATICAL & COMPUTATIONAL BIOLOGY).

HerDing: herb recommendation system to treat diseases using genes and chemicals.

  • Author :Wonjun Choi, Chan-Hun Choi, Young Ran Kim, Seon-Jong Kim, Chang-Su Na and Hyunju Lee
  • Published Date : 2016
  • Category : Bioinformatics and Text Mining 
  • Place of publication : Database-Oxford

 

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 diseases might 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 text-mining method. The HerDing website is free and open to all users, and there is no login requirement.

Database URL: http://combio.gist.ac.kr/herding

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