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Development of quantitative structure activity relationship (QSAR) model for disinfection byproduct (DBP) research: A review of methods and resources

Chen, B, Zhang, T, Bond, T and Gan, Y (2015) Development of quantitative structure activity relationship (QSAR) model for disinfection byproduct (DBP) research: A review of methods and resources Journal of Hazardous Materials, 299. pp. 260-279.

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Abstract

Quantitative structure–activity relationship (QSAR) models are tools for linking chemical activities with molecular structures and compositions. Due to the concern about the proliferating number of disinfection byproducts (DBPs) in water and the associated financial and technical burden, researchers have recently begun to develop QSAR models to investigate the toxicity, formation, property, and removal of DBPs. However, there are no standard procedures or best practices regarding how to develop QSAR models, which potentially limit their wide acceptance. In order to facilitate more frequent use of QSAR models in future DBP research, this article reviews the processes required for QSAR model development, summarizes recent trends in QSAR-DBP studies, and shares some important resources for QSAR development (e.g., free databases and QSAR programs). The paper follows the four steps of QSAR model development, i.e., data collection, descriptor filtration, algorithm selection, and model validation; and finishes by highlighting several research needs. Because QSAR models may have an important role in progressing our understanding of DBP issues, it is hoped that this paper will encourage their future use for this application.

Item Type: Article
Subjects : Civil Engineering
Authors :
NameEmailORCID
Chen, BUNSPECIFIEDUNSPECIFIED
Zhang, TUNSPECIFIEDUNSPECIFIED
Bond, Tt.bond@surrey.ac.ukUNSPECIFIED
Gan, YUNSPECIFIEDUNSPECIFIED
Date : 15 December 2015
Identification Number : 10.1016/j.jhazmat.2015.06.054
Copyright Disclaimer : © 2015 Elsevier B.V. All rights reserved.
Uncontrolled Keywords : Disinfection byproduct, QSAR/QSPR/QSTR/LFER, Descriptor filtration, Algorithm selection, Model validation
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 13:58
Last Modified : 18 May 2017 12:54
URI: http://epubs.surrey.ac.uk/id/eprint/840991

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