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.
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Document Type: Research Article
Publication date: 2010-10-01
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- Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.