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学科主题: 计算机化学与化学信息学
题名: SVM approach for predicting LogP
其他题名: SVM approach for predicting LogP
作者: Liao Q(廖泉) ; Yao JH(姚建华) ; Yuan SG(袁身刚)
通讯作者: 姚建华
刊名: Mol. Divers.
发表日期: 2006
卷: 10, 期:3, 页:301-309
收录类别: SCI
部门归属: Department of Computer Chemistry and Chemoinformatics, Shanghai Institute of Organic Chemistry, CAS
英文摘要: The logarithm of the partition coefficient between n-octanol and water (logP) is an important parameter for drug discovery. Based upon the comparison of several prediction logP models, I.e. Support Vector Machines (SVM), Partial Least Squares (PLS) and Multiple Linear Regression (MLR), the authors reported SVM model is the best one in this paper.
语种: 英语
相关网址: 查看原文
WOS记录号: WOS:000242137600004
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内容类型: 期刊论文
URI标识: http://ir.sioc.ac.cn/handle/331003/20617
Appears in Collections:计算机化学与化学信息学研究室_期刊论文

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Recommended Citation:
Liao Q,Yao JH,Yuan SG. SVM approach for predicting LogP[J]. Mol. Divers.,2006,10(3):301-309.
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