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The Effect of Variable Selection on the Non-linear Modeling of Oestrogen Receptor Binding

Gafourian, Travat, Cronin, Mark T.D. (2006) The Effect of Variable Selection on the Non-linear Modeling of Oestrogen Receptor Binding. QSAR and Combinatorial Sciences, 25 (10). pp. 824-835. ISSN 1611-020X. (doi:10.1002/qsar.200510153) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:10173)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1002/qsar.200510153

Abstract

Oestrogen Receptor Binding Affinity (RBA) is often used as a measure of the oestrogenicity

(QSAR) modellingof the bindingaf finities has been performed by three-dimensional

restricted, however, for chemically diverse sets of chemicals as the alignment of molecules

to the oestrogen receptor of a large diverse set of chemicals. To this end, various variable

stepwise regression, partial least squares and recursive partitioning (Formal Inference Based

Neural Networks (CPNNs) and Support Vector Machines (SVMs) and the models were

results showed that although there was a certain degree of similarities between the

SVM models varied. Although the variables selected by stepwise regression led to poor

selected by some of the FIRM methods were superior in CPNN.

Item Type: Article
DOI/Identification number: 10.1002/qsar.200510153
Subjects: Q Science
Divisions: Faculties > Sciences > Medway School of Pharmacy
Depositing User: Taravat Ghafourian
Date Deposited: 05 Sep 2008 20:02 UTC
Last Modified: 28 May 2019 13:47 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/10173 (The current URI for this page, for reference purposes)
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