Application of Multivariate Statistical Analysis in Amino Acids Compositions and Cold-Heat Nature of Traditional Chinese Medicine
10.11842/wst.2013.04.011
- VernacularTitle:氨基酸含量与寒热药性的多元统计分析
- Author:
Shuai FENG
;
Yang LIU
;
Feng LI
- Publication Type:Journal Article
- Keywords:
Cold-Hot medicine property;
amino acids;
discriminant analysis;
statistical identification model
- From:
World Science and Technology-Modernization of Traditional Chinese Medicine
2013;(4):672-679
- CountryChina
- Language:Chinese
-
Abstract:
This study was aimed to find the correlation between amino acid compositions and Cold-Heat Nature of traditional Chinese medicine (TCM) in order to provide basis for the research of TCM natural theory. A total of 17 kinds of amino acid were determined by application before column derivatization reaction and high-perfor-mance liquid chromatography (HPLC) and the tryptophan was determined by UV method. The data were collected for analysis by Fisher method in PAST software. The best statistical identification model was determined. And the Cold-Hot medicine property markers (CHMP-markers) were determined. The results showed that the discriminant function established by Fisher method based on 18 kinds of amino acid contents has good identification ability, and the accuracy of the Fisher discriminant analysis is 82%. Support vector machine (SVM) is the best statistical identification model . The cold and heat markers were analyzed by SVM . The cold nature material bases in-clude Glu, Gly, Arg, Thr, Ala, Tyr, Val, Ile and lys. And the heat nature material bases contain Asp, Ser, His, Pro, Met, Cys, Leu, Phe and Trp. It was concluded that there is relationship between 18 kinds of amino acid contents and the Cold-Heat nature of TCM .
