Literature DB >> 16490199

Quantitative structure-property relationships for pesticides in biopartitioning micellar chromatography.

Weiping Ma1, Feng Luan, Haixia Zhang, Xiaoyun Zhang, Mancang Liu, Zhide Hu, Botao Fan.   

Abstract

The retention factor (log k) in the biopartitioning micellar chromatography (BMC) of 79 heterogeneous pesticides was studied by quantitative structure-property relationships (QSPR) method. Heuristic method (HM) and support vector machine (SVM) method were used to build linear and nonlinear models, respectively. Compared the results of these two methods, those obtained by the SVM model are much better. For the test set, a predictive correlation coefficient (R) of 0.9755 and root-mean-square (RMS) error of 0.1403 were obtained. The proposed QSPR models, both by HM and SVM, contain the same descriptors that agree with the classical Abraham parameters of well-known linear solvation energy relationships (LSER).

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Year:  2006        PMID: 16490199     DOI: 10.1016/j.chroma.2006.01.136

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  2 in total

1.  In silico prediction of nematic transition temperature for liquid crystals using quantitative structure-property relationship approaches.

Authors:  Mohammad Hossein Fatemi; Mehdi Ghorbanzad'e
Journal:  Mol Divers       Date:  2009-03-27       Impact factor: 2.943

2.  Predicting retention times of naturally occurring phenolic compounds in reversed-phase liquid chromatography: a Quantitative Structure-Retention Relationship (QSRR) approach.

Authors:  Jamshed Akbar; Shahid Iqbal; Fozia Batool; Abdul Karim; Kim Wei Chan
Journal:  Int J Mol Sci       Date:  2012-11-20       Impact factor: 5.923

  2 in total

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