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

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.