The prediction of protein structural classes is beneficial to understanding folding patterns, functions and interactions of proteins. In this study, we proposed a feature selection-based method to accurately predict protein structural classes. Three datasets with sequence identity lower than 25% were used to test the prediction performance of the method. Through jackknife cross-validation, we have verified that the overall accuracies of these three datasets are 92.1%, 89.7% and 84.0%, respectively. The proposed method is more efficient and accurate than other existing methods. The present study will offer an excellent alternative to other methods for predicting protein structural classes.
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Ding, H., Lin, H., Chen, W. et al. Prediction of protein structural classes based on feature selection technique. Interdiscip Sci Comput Life Sci 6, 235–240 (2014). https://doi.org/10.1007/s12539-013-0205-6
- protein structural class
- feature selection technique
- support vector machine