title: Extreme self-organization in networks constructed from gene expression data.
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.
authors.affiliation: Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. feagrawa@wicc.weizmann.ac.il
authors.forename: Himanshu
authors.initials: H
authors.lastname: Agrawal
mesh_terms: D000230:Adenocarcinoma / Q000235:genetics*; D000465:Algorithms; D001943:Breast Neoplasms / Q000235:genetics*; D003110:Colonic Neoplasms / Q000235:genetics*; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling; D006801:Humans; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis