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• W2056574935 abstract "We study networks constructed from gene expression data obtained from many types of cancers. The networks are constructed by connecting vertices that belong to each others' list of K nearest neighbors, with K being an a priori selected non-negative integer. We introduce an order parameter for characterizing the homogeneity of the networks. On minimizing the order parameter with respect to K, degree distribution of the networks shows power-law behavior in the tails with an exponent of unity. Analysis of the eigenvalue spectrum of the networks confirms the presence of the power-law and small-world behavior. We discuss the significance of these findings in the context of evolutionary biological processes." @default.
• W2056574935 created "2016-06-24" @default.
• W2056574935 creator A5036792516 @default.
• W2056574935 date "2002-12-12" @default.
• W2056574935 modified "2023-10-18" @default.
• W2056574935 title "Extreme Self-Organization in Networks Constructed from Gene Expression Data" @default.
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• W2056574935 doi "https://doi.org/10.1103/physrevlett.89.268702" @default.
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