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High-Dimensional Descriptor Selection and Computational QSAR Modeling for Antitumor Activity of ARC-111 Analogues Based on Support Vector Regression (SVR)

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成果类型:
期刊论文
作者:
Zhou, Wei;Dai, Zhijun;Chen, Yuan;Wang, Haiyan;Yuan, Zheming*
通讯作者:
Yuan, Zheming
作者机构:
[Dai, Zhijun; Chen, Yuan; Yuan, Zheming; Zhou, Wei] Hunan Prov Key Lab Crop Germplasm Innovat & Utili, Changsha 410128, Hunan, Peoples R China.
[Yuan, Zheming; Zhou, Wei] Hunan Agr Univ, Coll Biosafety Sci & Technol, Hunan Prov Key Lab Biol & Control Plant Dis & Ins, Changsha 410128, Hunan, Peoples R China.
[Wang, Haiyan] Kansas State Univ, Dept Stat, Manhattan, KS 66506 USA.
通讯机构:
[Yuan, Zheming] H
Hunan Prov Key Lab Crop Germplasm Innovat & Utili, Changsha 410128, Hunan, Peoples R China.
语种:
英文
关键词:
ARC-111 analogues;QSAR;support vector regression;high-dimensional descriptor selection nonlinearly (HDSN) method;worst descriptor elimination multi-roundly (WDEM) method;RPMI8402
期刊:
International Journal of Molecular Sciences
ISSN:
1661-6596
年:
2012
卷:
13
期:
1
页码:
1161-1172
基金类别:
Science Foundation for Distinguished Young Scholars of Hunan Province, ChinaNational Natural Science Foundation of China (NSFC)National Science Fund for Distinguished Young Scholars [10JJ1005]; Specialized Research Fund for the Doctoral Program of Higher Education of ChinaSpecialized Research Fund for the Doctoral Program of Higher Education (SRFDP) [20114320120005]; Research Foundation of Education Bureau of Hunan Province, China [09C502]; Science Foundation for Talents from Hunan Agricultural University of China [07YJ05]
机构署名:
本校为其他机构
院系归属:
植物保护学院
摘要:
To design ARC-111 analogues with improved efficiency, we constructed the QSAR of 22 ARC-111 analogues with RPMI8402 tumor cells. First, the optimized support vector regression (SVR) model based on the literature descriptors and the worst descriptor elimination multi-roundly (WDEM) method had similar generalization as the artificial neural network (ANN) model for the test set. Secondly, seven and 11 more effective descriptors out of 2,923 features were selected by the high-dimensional descriptor selection nonlinearly (HDSN) and WDEM method, and the SVR models (SVR3 and SVR4) with these selected...

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