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

Chemometrics and Intelligent Laboratory Systems 145 (2015) 30–38 Contents lists available at ScienceDirect Chemometrics and Intelligent Laboratory Systems journal homepage: /locate/chemolab Nonlinear QSAR models with high-dimensional descriptor selection and SVR improve toxicity prediction and evaluation of phenols on Photobacterium phosphoreum a,b,c,1,2 d,2 b,2 b b e f Wei Zhou , Shubo Wu , Zhijun Dai , Yuan Chen , Yan Xiang , Jianrong Chen , Chunyu Sun , Qingming Zhou g,⁎, Zheming Yuan a,b,⁎⁎ a Hunan Provincial Key Laboratory of Crop Germplasm Innovation and Utilization, Hunan Agricultural University, Changsha 410128, PR China b Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests, Hunan Agricultural University, Changsha 410128, PR China c Department of Computer Sciences, Clemson University, Clemson, SC 29634, USA d College of Tourism, Central South University of Forestry and Technology, Changsha 410004, PR China e Department of Bioengineering Environmental Science, Changsha University, Changsha 410003, PR China f College of Life Science, Jilin Agricultural University, Changchun 130118, PR China g College of Agriculture, Hunan Agricultural University, Changsha 410128, PR China a r t i c l e i n f o a b s t r a c t Article history: Assessment of the risk of chemicals is an important task in the environmental protection. In this paper, we devel- Received 5 November 2014