TY - JOUR
ID - 19490
TI - Prediction of Proteins Structural Class in Two States Using the Hybrid Neural-Logistic Model
JO - Journal of Science,University of Tehran(not publish)
JA - JOS
LA - en
SN -
Y1 - 2008
PY - 2008
VL - 33
IS - 1
SP -
EP -
KW - Logistic Regression Model
KW - Artificial Neural Networks
KW - Protein Structure Prediction
DO -
N2 - 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
UR - https://jos.ut.ac.ir/article_19490.html
L1 - https://jos.ut.ac.ir/article_19490_768aa4016aed0733f2ac8dda24f7c88f.pdf
ER -