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A Novel community detecting algorithm in biological bipartite networks

Wei Liu, Yueyang Zhang, Ling Chen

The identification of communities is significant for the understanding of network structures and functions. In this paper, we propose a framework to address the problemofcommunity detection in bipartite networks based on principal components analysis.We show that bipartite network can be conveniently represented as linear graph formodule identification purposes. We apply the algorithm to real-world network data, showing that the algorithmsuccessfully findsmeaningful community structures of bipartite networks