Literature DB >> 12560968

Variable selection by an evolution algorithm using modified Cp based on MLR and PLS modeling: QSAR studies of carcinogenicity of aromatic amines.

Qi Shen1, Jian-Hui Jiang, Guo-Li Shen, Ru-Qin Yu.   

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.

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Year:  2002        PMID: 12560968     DOI: 10.1007/s00216-002-1668-1

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  1 in total

1.  Novel approach to evolutionary neural network based descriptor selection and QSAR model development.

Authors:  Zeljko Debeljak; Viktor Marohnić; Goran Srecnik; Marica Medić-Sarić
Journal:  J Comput Aided Mol Des       Date:  2006-04-11       Impact factor: 3.686

  1 in total

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