%0 Journal Article
%T Prediction of Proteins Structural Class in Two States Using the Hybrid Neural-Logistic Model
%J Journal of Science,University of Tehran(not publish)
%I
%Z
%D 2008
%\ 07/22/2008
%V 33
%N 1
%P -
%! Prediction of Proteins Structural Class in Two States Using the Hybrid Neural-Logistic Model
%K Logistic Regression Model
%K Artificial Neural Networks
%K Protein Structure Prediction
%R
%X The objective of the proposed study is predicting structural classes of proteins in two states (all-? and all-?). We used a two-stage hybrid model constructed of artificial neural networks (ANN) and logistic regression model (LRM). The LRM was initially used to extract the effective variables (n=7) from the generated structural variables (n=662) in order to simplify the structure of the ANN which intended to predict the structural classes of proteins. The predicting structural classes of proteins performed on one non-homologous mono-domain globular proteins data set (n=104). Among the 20 evaluated single amino acid composition frequencies Valine and Glycine frequency were statistically significant (P
%U https://jos.ut.ac.ir/article_19490_768aa4016aed0733f2ac8dda24f7c88f.pdf