论文信息 - Empirical Study on Modeling Quantitative Composition- Activity Relationships in Chinese Herbal Medicine

Empirical Study on Modeling Quantitative Composition- Activity Relationships in Chinese Herbal Medicine

Chinese herbal medicine (CHM) consists of up hundreds of chemical components, which have complex relationships with their bioactivities. Quantitatively modeling composition-activity relationships playing a crucial role in drug design from CHM. In this paper, principle component regression, partial least square regression and least square support vector machine were used to perform this task and exhibit high predictive precisions

Xuewei Wang | Yiyu Cheng | Yi Wang

[1] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[2] B. Kowalski,et al. Partial least-squares regression: a tutorial , 1986 .

[3] K. Lee. Research and Discovery Trends of Chinese Medicine in the New Century , 2004 .

[4] Cheng Yi. A Strategy for Studies on the Computational Theory and Methodology for Identifying the Composition-Activity Relationship of Chinese Medicine , 2003 .

[5] Johan A. K. Suykens,et al. Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.

[6] B. Lian. Chinese Medical Herbology and Pharmacology , 2003 .