Prediction of Protein-Protein Interaction Sites Based on a Novel Constructed Ensemble Classifiers

摘要

Protein-protein interaction sites are very essential for drug design and the prediction of protein-protein networks. A data set (S149) was adopted and 24 different features were extracted here. Sample sets were made up of these features. Then Radial Basis Functional neutral network that was optimized by Particle Swarm Optimization was selected as the single classifier. Finally, a novel method for constructing ensemble classifiers which was based on Principal Component Analysis was chose to process the training data set and it was compared with the Bagging and Adaboost. The final results showed that the new method was better and more effective.