To effectively predict the protein-protein interactions, an ensemble learning with artificial neural network and supporting vector machine as the individuals was used, and the feature selection of protein sequence was indicated by auto covariance and dipeptide composition.The prediction accuracy and AUC reached 92.16%, 94.38% and 0.972 5,0.981 5, respectively. A comparison among artificial neural network, supporting vector machine and ensemble learning showed that the ensemble learning revealed more superior performance than the others and can improve the prediction accuracy while avoiding the instability of prediction caused by sampling learning.
