Prediction β-hairpin motifs in enzyme protein using three methods

The authors use three methods, including matrix scoring algorithm, increment of diversity algorithm and Random Forest algorithm. They are used to predict β-hairpin motifs in the ArchDB-EC and ArchDB40 dataset. In the ArchDB-EC dataset, we obtain the accuracy of 68.5%, 79.8% and 84.3%, respectively. Matthew's correlation coefficient are 0.17, 0.61 and 0.63, respectively. Using same three methods in the ArchDB40 dataset, we obtain the accuracy and Matthew's correlation coefficient of 67.9% and 0.39, 75.2% and 0.51, 83.5% and 0.60, respectively. Experiments show that Random Forest algorithm for predicting β-hairpin motifs is best and the predictive results in ArchDB40 dataset are better than previous results.