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Many computational methods have been proposed for inference of protein-protein interactions as protein-protein interaction plays an important role in many cellular processes. One of methods is to infer protein-protein interactions based on domain-domain interactions, and the preliminary results have represented their feasibility. In this paper, we use the neural networks for predicting the strengths of protein interaction. This method is capable of exploring all possible interactions between domains and make predictions based on all the domains. Compared to expectation-maximization method and association method, the experimental results show that the proposed schemes can infer strengths of protein-protein interactions with better performances.