title: Study on the screening of molecular structure parameter in QSAR model.
abstract: Based on the analysis of information flow through the Artificial Neural Network (ANN), a new screening rule of the molecular structure parameter in Quantitative Structure-Activity Relationship (QSAR) was presented by comparing of the values of connection weights and biases of the ANN model. The result showed that model quality and prediction ability of QSAR model, which was constructed by screening structural parameter with ANN, were better than by the method with MLR. The method established the foundation for further study in the mechanism research of the bio-toxicity of organic chemicals.
authors.affiliation: Department of Environmental Science & Engineering, Harbin Institute of Technology, China.
authors.forename: Da-Wen
authors.initials: DW
authors.lastname: Gao
authors.forename: Peng
authors.initials: P
authors.lastname: Wang
authors.forename: Lei
authors.initials: L
authors.lastname: Yang
authors.forename: Yong-Zhen
authors.initials: YZ
authors.lastname: Peng
authors.forename: Hong
authors.initials: H
authors.lastname: Liang
mesh_terms: D000818:Animals; D004785:Environmental Pollutants / Q000633:toxicity*; D005544:Forecasting; D006801:Humans; D015394:Molecular Structure; D016571:Neural Networks, Computer; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D013329:Structure-Activity Relationship
chemical_list: D004785:Environmental Pollutants