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 |
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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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