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Prediction of retention times for a large set of pesticides based on improved gene expression programming

Authors:

Kejun Zhang,

Shouqian Sun,

Hongzong SiAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 1725 - 1726

https://doi.org/10.1145/1389095.1389429

Published: 12 July 2008 Publication History

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Abstract

The purpose of the paper is to present a novel way to building Quantitative structure-retention relationship (QSRR) models. Studies was reported for predicting the retention times (RTs) of 110 pesticides which were detected by gas chromatography (GC) with mass selective detector (MSD). Chemical descriptors were calculated from the molecular structure of pesticides and the QSRR models of RTs with descriptors was built using the heuristic method (HM) and Improved Gene Expression Programming (IGEP), respectively. The obtained linear model of HM had a correlation coefficient R² = 0.913, with a root mean square error (RMS) S² of 0.0387 for the training set, while R2 =0.907, and RMS =0.0408 for the test set. The nonlinear model by IGEP gave better results: for the training set R² = 0.971, S² = 0.0176 and for the test set R² =0.951, S² =0.0267. The prediction results from nonlinear model are in agreement with the experimental values The QSRR model also reveals that the gas chromatographic RTs are associated with physicochemical property of pesticides.

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Cited By

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Guo ZWu ZDong XZhang KWang SLi Y(2014)Component Thermodynamical Selection Based Gene Expression Programming for Function FindingMathematical Problems in Engineering10.1155/2014/9150582014:1Online publication date: 16-Jan-2014
https://doi.org/10.1155/2014/915058
Browne Ndos Santos M(2010)Adaptive representations for improving evolvability, parameter control, and parallelization of gene expression programmingApplied Computational Intelligence and Soft Computing10.1155/2010/4090452010(1-19)Online publication date: 1-Jan-2010
https://dl.acm.org/doi/10.1155/2010/409045

Index Terms

Prediction of retention times for a large set of pesticides based on improved gene expression programming
1. Applied computing
2. Information systems
  1. Information systems applications
    1. Decision support systems
      1. Expert systems

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GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

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Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

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Guo ZWu ZDong XZhang KWang SLi Y(2014)Component Thermodynamical Selection Based Gene Expression Programming for Function FindingMathematical Problems in Engineering10.1155/2014/9150582014:1Online publication date: 16-Jan-2014
https://doi.org/10.1155/2014/915058
Browne Ndos Santos M(2010)Adaptive representations for improving evolvability, parameter control, and parallelization of gene expression programmingApplied Computational Intelligence and Soft Computing10.1155/2010/4090452010(1-19)Online publication date: 1-Jan-2010
https://dl.acm.org/doi/10.1155/2010/409045

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Automated retention time prediction of new psychoactive substances in gas chromatography

Theoretical analysis on retention behavior of pigments in reversed-phase high-performance liquid chromatographic (HPLC)

Prediction of glycan structures from gene expression data based on glycosyltransferase reactions

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