Superfamilies of evolved and designed networks.

by: R Milo, S Itzkovitz, N Kashtan, R Levitt, S Shen-Orr, I Ayzenshtat, M Sheffer, U Alon

Science, Vol. 303, No. 5663. (5 March 2004), pp. 1538-1542.

View FullText article

DOI, HighWire, Pubmed, Hubmed

Reviews [Write a review of this article]

There are no reviews of this article

Find related articles from these CiteULike users

galyardt, ChaTo, lfriedl, alexg, yish, balicea, ssb, ddahlem, cmm, j3xucite, donade, bigbossman, gurkanbebek, shenorr, ltabourier, michaelmampaey, kdl (group), mathgamespatterns (group), dtl (group), vds-arg (group), eni (group), FAB-lab (group), ADMiRes (group), zibuyu, tnhh, karfunkel

Find related articles with these CiteULike tags

2004, biological, clustering, complexity, complex-systems, datamining, eni, graph, graph_based_analysis, graph-characterization, graphs, informatics, modeling-and-simulation, motif, motifs, motif_search, my, network, network-analysis, networks, network-structure, no-tag, papers, social, social-networks

Abstract

Complex biological, technological, and sociological networks can be of very different sizes and connectivities, making it difficult to compare their structures. Here we present an approach to systematically study similarity in the local structure of networks, based on the significance profile (SP) of small subgraphs in the network compared to randomized networks. We find several superfamilies of previously unrelated networks with very similar SPs. One superfamily, including transcription networks of microorganisms, represents "rate-limited" information-processing networks strongly constrained by the response time of their components. A distinct superfamily includes protein signaling, developmental genetic networks, and neuronal wiring. Additional superfamilies include power grids, protein-structure networks and geometric networks, World Wide Web links and social networks, and word-adjacency networks from different languages.

@article{citeulike:363614, abstract = {Complex biological, technological, and sociological networks can be of very different sizes and connectivities, making it difficult to compare their structures. Here we present an approach to systematically study similarity in the local structure of networks, based on the significance profile (SP) of small subgraphs in the network compared to randomized networks. We find several superfamilies of previously unrelated networks with very similar SPs. One superfamily, including transcription networks of microorganisms, represents "rate-limited" information-processing networks strongly constrained by the response time of their components. A distinct superfamily includes protein signaling, developmental genetic networks, and neuronal wiring. Additional superfamilies include power grids, protein-structure networks and geometric networks, World Wide Web links and social networks, and word-adjacency networks from different languages.}, address = {Departments of Molecular Cell Biology, Physics of Complex Systems, and Computer Science, Weizmann Institute of Science, Rehovot 76100, Israel.}, author = {Milo, R. and Itzkovitz, S. and Kashtan, N. and Levitt, R. and Shen-Orr, S. and Ayzenshtat, I. and Sheffer, M. and Alon, U. }, citeulike-article-id = {363614}, doi = {http://dx.doi.org/10.1126/science.1089167}, issn = {1095-9203}, journal = {Science}, keywords = {my, papers}, month = {March}, number = {5663}, pages = {1538--1542}, posted-at = {2006-09-17 15:36:52}, priority = {0}, title = {Superfamilies of evolved and designed networks.}, url = {http://dx.doi.org/10.1126/science.1089167}, volume = {303}, year = {2004} }

RIS record

TY - JOUR ID - citeulike:363614 L3 - citeulike-article-id:363614 TI - Superfamilies of evolved and designed networks. JF - Science VL - 303 IS - 5663 SP - 1538 EP - 1542 AD - Departments of Molecular Cell Biology, Physics of Complex Systems, and Computer Science, Weizmann Institute of Science, Rehovot 76100, Israel. SN - 1095-9203 N2 - Complex biological, technological, and sociological networks can be of very different sizes and connectivities, making it difficult to compare their structures. Here we present an approach to systematically study similarity in the local structure of networks, based on the significance profile (SP) of small subgraphs in the network compared to randomized networks. We find several superfamilies of previously unrelated networks with very similar SPs. One superfamily, including transcription networks of microorganisms, represents "rate-limited" information-processing networks strongly constrained by the response time of their components. A distinct superfamily includes protein signaling, developmental genetic networks, and neuronal wiring. Additional superfamilies include power grids, protein-structure networks and geometric networks, World Wide Web links and social networks, and word-adjacency networks from different languages. KW - my KW - papers AU - Milo, R AU - Itzkovitz, S AU - Kashtan, N AU - Levitt, R AU - Shen-Orr, S AU - Ayzenshtat, I AU - Sheffer, M AU - Alon, U PY - 2004/03/05/ UR - http://dx.doi.org/10.1126/science.1089167 ER -

RIS BibTeX