Phys Rev Lett. 2002 Dec 23;89(26):268702. Epub 2002 Dec 12.

Extreme self-organization in networks constructed from gene expression data.

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Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. feagrawa@wicc.weizmann.ac.il

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.

PMID:: 12484863; [PubMed - indexed for MEDLINE]

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Extreme self-organization in networks constructed from gene expression data.
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Extreme self-organization in networks constructed from gene expression data.

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