Extracting herb-compound relations with quantity information from biomedical literature = 생의학 문헌으로부터 정량 정보를 포함한 약재-구성성분 관계 추출

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 447
  • Download : 0
To develop the new drug and design strategies for diseases, it is required to understand the mechanism of herbal medicine. For this, it is important to construct networks of integrative relations among diseases, herbs, compounds and genes. Among these relations, it is necessary to understand the quantity information of compounds in herbs for high-resolution analysis about herbs have different effects to distinct phenotype. Most of this knowledge is available from the biomedical literature. In this study, we develop a machine-learning based text-mining model to extract herb-compound relations with quantity information from the biomedical literature.
Advisors
Lee, Kwang Hyungresearcher이광형researcher
Description
한국과학기술원 :바이오및뇌공학과,
Publisher
한국과학기술원
Issue Date
2017
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 바이오및뇌공학과, 2017.8,[iii, 45 p. :]

Keywords

Machine-learning▼aInformation extraction▼aText-mining▼aBioinformatics▼aRelation extraction; 기계학습▼a정보 추출▼a텍스트마이닝▼a바이오정보학▼a관계 추출

URI
http://hdl.handle.net/10203/242996
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=718596&flag=dissertation
Appears in Collection
BiS-Theses_Master(석사논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0