Abstract
In this paper, we present a supervised learning-based method for predicting protein complexes in protein interaction network. The method extracts rich features from protein interaction network to train a Regression model, which is then used for the cliques filtering, growth, and candidate complex filtering. The experimental results on several protein interaction networks show that our method outperforms other state-of-the-art protein complex detection methods.