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Computational methods for Traditional Chinese Medicine: a survey
Suryani Lukman1, Yulan He, Siu-Cheung Hui
1Department of Chemistry, University of Cambridge, Cambridge, UK. lukman1a@gmail.com
Computer Methods and Programs in Biomedicine
|November 7, 2007
Summary
Computational methods are advancing Traditional Chinese Medicine (TCM) research, offering insights into formulations, diagnosis, and component analysis for future discoveries.
Area of Science:
- Computational biology
- Bioinformatics
- Traditional Chinese Medicine research
Background:
- Traditional Chinese Medicine (TCM) is increasingly studied using computational techniques.
- Existing research highlights challenges and progress in computational TCM.
- Understanding TCM formulations and their integration with Western medicine is crucial.
Purpose of the Study:
- To review computational approaches applied to Traditional Chinese Medicine.
- To analyze databases, classification systems, and mining tools for TCM formulations.
- To examine computational diagnostic methods and expert systems in TCM.
Main Methods:
- Literature review of computational methods in TCM.
- Analysis of TCM formulation databases and integration strategies.
- Evaluation of computational diagnostic techniques (inspection, auscultation, pulse analysis).
- Review of TCM expert systems and component-gene/protein relationship studies.
Main Results:
- Computational methods offer diverse approaches to TCM research.
- Databases and mining tools facilitate the study of TCM formulations.
- Computational diagnosis and expert systems present both benefits and drawbacks.
- Exploration of TCM component relationships and their molecular underpinnings is advancing.
Conclusions:
- Computational approaches are significantly advancing TCM research.
- This review provides a summary of current progress and future directions.
- Further knowledge discovery in TCM is facilitated by these computational methods.