Prediction of Cyclin Proteins Using Chou's Pseudo Amino Acid Composition

There are different types of cyclins, which are active during the cell cycle and enable cyclin-dependent kinases to phosphorylate different substrates. Since there is not much similarity between amino acid sequences of cyclins, predicting these proteins is an important job. This paper presents a bioinformatics classifier to predict cyclins based on Chou's pseudo amino acid composition. Analysis of the results by StAR, which is a program for the analysis of ROC curves, showed that accuracy of the approach was 83.53% (AUC=89.44%). The present work demonstrates that the method can provide useful information for predicting cyclins.