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A similarity based framework for the targeted selection of herbs with similar efficacy by Sang-Jun Yea(KSE Ph.D candidate)


Please attend an open presentation of KSE Ph.D student


  ■ Date & Time : 5 August 2016(Fri), P.M 2:30~3:30


  ■ Place : # 1222 Seminar Room, E2-1


  ■ Speaker : 예상준(Sang-Jun Yea)


  ■ Title : A similarity based framework for the targeted selection of herbs with similar efficacy


  ■ Abstract : Natural products have long been the most important source of ingredients in the discovery of new drugs. Moreover, since the Nagoya Protocol, finding alternative herbs with similar efficacy has become a very important issue in traditional medicine. Although random selection is a common method of finding ethno-medicinal herbs with similar efficacy, it proved to be less effective; therefore, this study aims to develop comprehensive a similarity based framework for targeted selection of herbs with similar efficacy adpting non-curated and curated modern scientific biomedical knowledge. In preliminary study, we proposed the method adopting similarity based on medical subject headings (MeSH) between articles in MEDLINE which is the largest non-curated biomedical database. In order to evaluate the proposed method, we built up three kinds of validation datasets which contain lists of original herbs and corresponding herbs with similar efficacy. The average area under curve (AUC) of the proposed method was found to be about 200% ~ 2500% larger than the random selection method. It was also found that the AUC of the proposed method either remained the same or increased slightly in all three validation datasets as the search range was increased. In order to overcome the limitation and improving the performance of preliminary study using curated modern scientific biomedical knowledge and prediction model with various similarity measures, we propose novel framework which is composed of four different layers: link layer, extract layer, similarity layer and model layer.





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