title: Variable selection by an evolution algorithm using modified Cp based on MLR and PLS modeling: QSAR studies of carcinogenicity of aromatic amines.
abstract: The variable selection in QSAR studies by MLR and PLS modeling has been performed using the evolution algorithm (EA). The Cp statistic has been modified and used as the objective function in the EA search for different combinations of molecular descriptors. For MLR modeling a few information-rich descriptors are selected for model formulation. In PLS modeling, the proposed procedure selects a relatively large number of information-containing descriptors, and a PLS model is formulated based on a few latent variables, which are linear combinations of the selected descriptors. The proposed procedures were used for the prediction of carcinogenicity of aromatic amines.
authors.affiliation: State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, 410082 Changsha, China.
authors.forename: Qi
authors.initials: Q
authors.lastname: Shen
authors.forename: Jian-Hui
authors.initials: JH
authors.lastname: Jiang
authors.forename: Guo-Li
authors.initials: GL
authors.lastname: Shen
authors.forename: Ru-Qin
authors.initials: RQ
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D000588:Amines / Q000737:chemistry* / Q000633:toxicity*; D002273:Carcinogens / Q000737:chemistry* / Q000633:toxicity*; D021281:Quantitative Structure-Activity Relationship
chemical_list: D000588:Amines; D002273:Carcinogens