An accurate nonlinear QSAR model for the antitumor activities of chloroethylnitrosoureas using neural networks

Journal of Molecular Graphics and Modelling

Volumn 29, Issue 6, 2011, Pages 826-833

  Qin, Yu ^a   Deng, Hongfei ^a   Yan, Hong ^a   Zhong, Rugang ^a  

^a BEIJING UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Chloroethylnitrosourea; Molecular descriptor; Neural network; Nonlinearity; QSAR

Indexed keywords

ALKYLATING AGENTS; ANTI-TUMOR ACTIVITIES; BIOLOGICAL ACTIVITIES; CHLOROETHYLNITROSOUREA; INPUT VARIABLES; MOLECULAR DESCRIPTOR; MOLECULAR DESCRIPTORS; MULTIPLE LINEAR REGRESSION MODELS; NON-LINEAR MODEL; NON-LINEARITY; QSAR; QSAR MODEL; QSAR STUDIES; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP STUDIES; YIELD PREDICTION;

LINEAR REGRESSION; MOLECULAR GRAPHICS; NEURAL NETWORKS;

COMPUTATIONAL CHEMISTRY;

CHLOROETHYLNITROSOUREA;

ACCURACY; ANTINEOPLASTIC ACTIVITY; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL ACTIVITY; HYDROPHILICITY; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION;

ANTINEOPLASTIC AGENTS; ETHYLNITROSOUREA; MODELS, MOLECULAR; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 79953290551     PISSN: 10933263     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmgm.2011.01.007     Document Type: Article

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