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The study on protein-protein interactions is rapidly increasing; one of the most important findings of such study is the observation of hub proteins that play vital roles in all organisms. Identifying hub proteins may provide more information on essential proteins and lead to more efficient methods for their prediction. Here, we proposed a new network topological-based method for prediction of hub proteins in Saccharomyces cerevisiae (baker's yeast). The method, HP3NN (Hub Protein Prediction using Probabilistic Neural Network), has successfully predicts the hub proteins with accuracy of 95% (sensitivity of 1.0 and specificity of 0.89).