A new protein structure classification model

Protein structure prediction is an important area of research in bioinformatics. In this paper, we select the features of correlation coefficient sequence and special amino acid composition. The support vector machine and a particular framework of ECOC are employed as classification model. To evaluate the efficiency of the proposed method we choose three benchmark protein sequence datasets (25PDB, 40PDB and ASTRAL) as the test dataset. The final results show that our method is efficient for protein structure prediction.