Toxicity of ionic liquids: Database and prediction via quantitative structure-activity relationship method

Journal of Hazardous Materials

Volumn 278, Issue , 2014, Pages 320-329

  Zhao, Yongsheng ^a,b   Zhao, Jihong ^b   Huang, Ying ^a   Zhou, Qing ^a   Zhang, Xiangping ^a   Zhang, Suojiang ^a  

^a INSTITUTE OF PROCESS ENGINEERING   (China)

^b ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY   (China)

Author keywords

Ionic liquids; Multiple linear regression (MLR); QSAR; Support vector machine (SVM); Toxicity

Indexed keywords

CELL CULTURE; COMPUTATIONAL CHEMISTRY; DATABASE SYSTEMS; DYES; FORECASTING; HEURISTIC METHODS; IONIC LIQUIDS; LINEAR REGRESSION; MEAN SQUARE ERROR; MOLECULAR GRAPHICS; ORGANIC CHEMICALS; SUPPORT VECTOR MACHINES;

IONIC LIQUID (ILS); MULTIPLE LINEAR REGRESSIONS; NON-LINEAR MODEL; QSAR; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP METHODS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS; ROOT MEAN SQUARE ERRORS; SQUARED CORRELATION COEFFICIENTS;

TOXICITY;

IONIC LIQUID;

DATABASE; EXPERIMENTAL STUDY; PREDICTION; QUANTITATIVE ANALYSIS; RODENT; TOXICITY;

ALGORITHM; ANIMAL CELL; ARTICLE; ATOM; CONTROLLED STUDY; DATA BASE; LEUKEMIA CELL LINE; MOLECULE; NONHUMAN; PREDICTION; QUALITATIVE ANALYSIS; QUANTITATIVE ANALYSIS; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RAT; SUPPORT VECTOR MACHINE; ANIMAL; CHEMISTRY; FACTUAL DATABASE; STATISTICAL MODEL; THEORETICAL MODEL; TUMOR CELL LINE;

ANIMALS; CELL LINE, TUMOR; DATABASES, FACTUAL; IONIC LIQUIDS; LINEAR MODELS; MODELS, THEORETICAL; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; RATS; SUPPORT VECTOR MACHINES;

EID: 84903615865     PISSN: 03043894     EISSN: 18733336     Source Type: Journal    
DOI: 10.1016/j.jhazmat.2014.06.018     Document Type: Article

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