Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective. (11th June 2017)
- Record Type:
- Journal Article
- Title:
- Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective. (11th June 2017)
- Main Title:
- Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective
- Authors:
- Gu, Shuo
Pei, Jianfeng - Other Names:
- Rahman Khalid Academic Editor.
- Abstract:
- Abstract : With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.
- Is Part Of:
- Evidence-based complementary and alternative medicine. Volume 2017(2017)
- Journal:
- Evidence-based complementary and alternative medicine
- Issue:
- Volume 2017(2017)
- Issue Display:
- Volume 2017, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 2017
- Issue:
- 2017
- Issue Sort Value:
- 2017-2017-2017-0000
- Page Start:
- Page End:
- Publication Date:
- 2017-06-11
- Subjects:
- Alternative medicine -- Periodicals
615.505 - Journal URLs:
- http://ecam.oupjournals.org ↗
http://www.ncbi.nlm.nih.gov/pmc/journals/241/ ↗
http://www.hindawi.com/journals/ecam/ ↗ - DOI:
- 10.1155/2017/7198645 ↗
- Languages:
- English
- ISSNs:
- 1741-427X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3831.036630
British Library HMNTS - ELD Digital store - Ingest File:
- 23591.xml