Zakarya, D. and Larfaoui, E.M. and Boulaamail, A. and Tollabi, M. and Lakhlifi, T. (1998) QSARs for a series of inhibitory anilides. Chemosphere, 36 (13). pp. 2809-2818.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

Neural network was applied to study a series of anilide herbicides inhibiting photosystem II (PSII). The molecules were encoded by a set of dimensional parameters. The model established using a back-propagation algorithm of neural network (r = 0.967; n = 76) was superior to that obtained using multiple linear regression (r = 0.922; n = 76). The descriptor's contributions to the PS II inhibitory activity pI50 were calculated by a method which consists in analysing the statistical coefficients between observed and calculated pI50 using neural network, when a descriptor is taken off. The results obtained were interpreted in terms of interactions molecule-receptor site.

Item Type: Article
Uncontrolled Keywords: anilide; herbicide, algorithm; article; artificial neural network; partition coefficient; photosystem II; quantitative structure activity relation; soil pollution
Subjects: Chemistry
Divisions: SCIENTIFIC PRODUCTION > Chemistry
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:45
URI: http://eprints.umi.ac.ma/id/eprint/2108

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