Prediction of herbal multi-component drug effect based on multi-target analysis = 다중표적 분석에 기반한 다성분 천연물신약의 효능 예측

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Traditional Chinese medicines are regarded as promising source for drug development, since they are relatively safe and their therapeutic effect are previously known, thanks to accumulated trial experiences for over-thousand years. However, its integrated mechanism of action in multi-component level is still unknown.In this research, we developed a system that predict the effect of the multicomponent drug based on multi-target analysis of molecular information. We have integrated biological databases (KEGG, ChEMBL) to obtain drug-related pathways. Next, pathway entities were divided into more specifically defined smaller sub-pathway named product oriented sub-pathway (PSP). From PSP-linked to metabolite sets, drug-affected terms in physiological level were obtained through co-occurrence analysis in PubMed.We have performed a case study for the complex herbal drugs composed of Corydalis tuber and Pharbitis seed. Resulted physiological function terms showed significant similarity with previously known functions of the TCM ingredients.
Advisors
Lee, Do-Heonresearcher이도헌
Description
한국과학기술원 : 바이오및뇌공학과,
Publisher
한국과학기술원
Issue Date
2014
Identifier
568885/325007  / 020123051
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 바이오및뇌공학과, 2014.2, [ vi, 34 p. ]

Keywords

drug development; 텍스트마이닝; 네트워크; KEGG; 생물학적 경로; 천연물신약; TCM; herbal medicine; pathway; KEGG; network analysis; text mining; 신약개발

URI
http://hdl.handle.net/10203/196317
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=568885&flag=dissertation
Appears in Collection
BiS-Theses_Master(석사논문)
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