Prediction of protein homo-oligomer types with a novel approach of glide zoom window feature extraction

A novel approach of glide zoom window feature extraction based on protein sequence was proposed for predicting protein homo-oligomers. Based on the concept of glide zoom window, three feature vectors of amino acids distance sum, amino acids mean distance and amino acids distribution, were extracted. A series of feature sets were constructed by combing these feature vectors with amino acids composition to form pseudo amino acid compositions (PseAAC). The support vector machine (SVM) was used as base classifier. The 73.19% total accuracy is arrived in jackknife test, which is 7.87% higher than that of conventional amino acid composition method. The results show that the novel feature extraction method of glide zoom window is effective and feasible, and the feature vectors extracted with this method may contain more protein structure information.