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The web-server PPI is used to predict the protein-protein interaction. In this study,a new model is proposed for PPIs prediction. Based on the physicochemical descriptors, a protein could be converted into several digital signals and then wavelet transform was used to analyze them.a two-layer ensemble learning framework was proposed. The random forests algorithm was adopted to conduct prediction using each descriptor features and the final result was gotten by integrating all the random forests results via voting.

To obtain the predicted result with the anticipated success rate, the entire sequence of the query protein rather than its fragment should be used as an input.