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Community Detection in Disease-Gene Network Based on Principal Component Analysis

Wei Liu()Ling Chen
Department of Computer Science, Information Science and Technology College, Yangzhou University, Yangzhou 225127, China
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Abstract

The identification of communities is imperative in the understanding of network structures and functions. Using community detection algorithms in biological networks, the community structure of biological networks can be determined, which is helpful in analyzing the topological structures and predicting the behaviors of biological networks. In this paper, we analyze the diseasome network using a new method called disease-gene network detecting algorithm based on principal component analysis, which can be used to investigate the connection between nodes within the same group. Experimental results on real-world networks have demonstrated that our algorithm is more efficient in detecting community structures when compared with other well-known results.

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Tsinghua Science and Technology
Pages 454-461
Cite this article:
Liu W, Chen L. Community Detection in Disease-Gene Network Based on Principal Component Analysis. Tsinghua Science and Technology, 2013, 18(5): 454-461. https://doi.org/10.1109/TST.2013.6616519
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