Nonlinear QSAR models with high-dimensional descriptor selection and SVR improve toxicity prediction and evaluation of phenols on Photobacterium phosphoreum

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Zhou, Wei;Wu, Shubo;Dai, Zhijun;Chen, Yuan;Xiang, Yan;...

通讯作者：

Zhou, Qingming

作者机构：

[Yuan, Zheming; Zhou, Wei] Hunan Agr Univ, Hunan Prov Key Lab Crop Germplasm Innovat & Utili, Changsha 410128, Hunan, Peoples R China.

[Yuan, Zheming; Dai, Zhijun; Chen, Yuan; Xiang, Yan; Zhou, Wei] Hunan Agr Univ, Hunan Prov Key Lab Biol & Control Plant Dis & Ins, Changsha 410128, Hunan, Peoples R China.

[Zhou, Wei] Clemson Univ, Dept Comp Sci, Clemson, SC 29634 USA.

[Wu, Shubo] Cent South Univ Forestry & Technol, Coll Tourism, Changsha 410004, Hunan, Peoples R China.

[Chen, Jianrong] Changsha Univ, Dept Bioengn & Environm Sci, Changsha 410003, Hunan, Peoples R China.

通讯机构：

[Zhou, Qingming] H

Hunan Agr Univ, Coll Agr, Changsha 410128, Hunan, Peoples R China.

语种：

英文

关键词：

High-dimensional descriptor selection;Phenol;Photobacterium phosphoreum;QSAR;SVR

期刊：

Chemometrics and Intelligent Laboratory Systems

ISSN：

0169-7439

年：

2015

卷：

145

页码：

30-38

DOI：

10.1016/j.chemolab.2015.04.010

基金类别：

National Natural Science Foundation for Young Scientists of ChinaNational Natural Science Foundation of China (NSFC) [31301388]; China Postdoctoral Science FoundationChina Postdoctoral Science Foundation [2014M562109]; Hunan Provincial Natural Science Foundation of ChinaNatural Science Foundation of Hunan Province [14JJ3092]; Science and Technology Program of Hunan Provincial Science & Technology Department [2014GK3046]

机构署名：

本校为第一且通讯机构

院系归属：

农学院

植物保护学院

摘要：

Assessment of the risk of chemicals is an important task in the environmental protection. In this paper, we developed quantitative structure-activity relationship (QSAR) methods to evaluate the toxicity of phenol to Photobacterium phosphoreum, which is an important indicator for water quality. We first built support vector regression (SVR) model using three descriptors, and the SVR model (t=2) had the highest external prediction ability (MSEext=0.068, Qext2=0.682), about 40% higher than literature model's. Second, to identify more effective des...

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Nonlinear QSAR models with high-dimensional descriptor selection and SVR improve toxicity prediction and evaluation of phenols on Photobacterium phosphoreum

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