Prediction of atmospheric degradation data for POPs by gene expression programmi

Prediction of atmospheric degradation data for POPs by gene expression programming.
(PMID:18853297)

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Luan F, Find all citations by this author (default).
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Zhang XY

Department of Applied Chemistry, Yantai University, Yantai, Shandong, P.R. China. fluan@sina.com
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SAR and QSAR in Environmental Research [2008, 19(5-6):465-79]


Type:  Journal Article
DOI: 10.1080/10629360802348845

Abstract

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Quantitative structure-activity relationship models for the prediction of the mean and the maximum atmospheric degradation half-life values of persistent organic pollutants were developed based on the linear heuristic method (HM) and non-linear gene expression programming (GEP). Molecular descriptors, calculated from the structures alone, were used to represent the characteristics of the compounds. HM was used both to pre-select the whole descriptor sets and to build the linear model. GEP yielded satisfactory prediction results: the square of the correlation coefficient r(2) was 0.80 and 0.81 for the mean and maximum half-life values of the test set, and the root mean square errors were 0.448 and 0.426, respectively. The results of this work indicate that the GEP is a very promising tool for non-linear approximations.

http://ukpmc.ac.uk/abstract/MED/18853297