Extreme self-organization in networks constructed from gene expression data

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

2002-07-17

arxiv.org/abs/cond-mat/0207409v2

Phys. Rev. Lett. 89, 268702 (2002)

Physics

Condensed Matter

Soft Condensed Matter

4 pages including 3 eps figures, revtex. Revisions as in published version

Scientific paper

10.1103/PhysRevLett.89.268702

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.

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