Classify vertebrate hemoglobin proteins by incorporating the evolutionary information into the general PseAAC with the hybrid approach

Abstract

Hemoglobin is an oxygen-binding protein widely present in all kingdoms of life from prokaryotic to eukaryotic, but well established in the vertebrate system. An attempt was made to determine the Vertebrate hemoglobin (VerHb) protein on their animal classifications, based on general pseudo amino acid composition (PseAAC)'s evolutionary profiles and hybrid approach. The support vector machine (SVM) has been applied to develop all models, the prediction results further compared according to their animal classification. The performance of the approaches estimated using five-fold cross-validation techniques. The prediction performance was further investigated by receiver operating characteristic (ROC) and prediction score graphs. The prediction accuracy (ACC), sensitivity (SN) and specificity (SP) were examined to find the accurate predictions on the threshold level. Based on the approach, a web-tool has been developed for identifying the VerHb proteins.