| 支持向量分类算法在5-HT3受体拮抗剂的构效关系研究中的应用 |
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| 引用本文： | 杨善升,陆文聪,纪晓波,陈念贻.支持向量分类算法在5-HT3受体拮抗剂的构效关系研究中的应用[J].上海大学学报(英文版),2006,10(4):366-370. |
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| 作者姓名： | 杨善升 陆文聪 纪晓波 陈念贻 |
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| 作者单位： | Department of Chemistry, College of Sciences, Shanghai University, Shanghai 200444, P.R. China |
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| 摘 要： | In this work, support vector classification （SVC） algorithm was used to build structure-activity relationship （SAR） model of the 5-hydroxytryptamine type 3 （5-HT3 ） receptor antagonists with 26 compounds. In a benchmark test, SVC was compared with several techniques of machine learning currently used in the field. The prediction performance of the model was discussed on the basis of the leave-one-out cross-validation. The results show that the accuracy of prediction of SVC model was higher than those of back propagation artificial neural network （BP ANN）, K-nearest neighbor （KNN） and Fisher methods.
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| 关 键 词： | 支持向量分类 结构-活性关系 化学计量学 5-HT3受体拮抗体 |
| 文章编号： | 1007-6417（2006）04-0366-05 |
| 收稿时间： | 2004-09-28 |
| 修稿时间： | 2005-04-12 |
Support vector classification for SAR of 5-HT3 receptor antagonists |
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| Shan-sheng Yang Ph. D. Candidate,Wen-cong Lu,Xiao-bo Ji,Nian-yi Chen.Support vector classification for SAR of 5-HT3 receptor antagonists[J].Journal of Shanghai University(English Edition),2006,10(4):366-370. |
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| Authors: | Shan-sheng Yang Ph D Candidate Wen-cong Lu Xiao-bo Ji Nian-yi Chen |
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| Abstract: | In this work, support vector classification (SVC) algorithm was used to build structure-activity relationship (SAR) model
of the 5-hydroxytryptamine type 3 (5-HT3) receptor antagonists with 26 compounds. In a benchmark test, SVC was compared with several techniques of machine learning
currently used in the field. The prediction performance of the model was discussed on the basis of the leave-one-out cross-validation.
The results show that the accuracy of prediction of SVC model was higher than those of back propagation artificial neural
network (BP ANN), K-nearest neighbor (KNN) and Fisher methods.
Project supported by National Natural Science Foundation of China(Grant No. 20373040) |
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| Keywords: | support vector classification structure-activity relationship chemometrics 5-HT3 receptor antagonists |
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