Superfamilies of evolved and designed networks

被引:1000
作者
Milo, R
Itzkovitz, S
Kashtan, N
Levitt, R
Shen-Orr, S
Ayzenshtat, I
Sheffer, M
Alon, U [1 ]
机构
[1] Weizmann Inst Sci, Dept Mol Cell Biol, IL-76100 Rehovot, Israel
[2] Weizmann Inst Sci, Dept Phys Complex Syst, IL-76100 Rehovot, Israel
[3] Weizmann Inst Sci, Dept Comp Sci, IL-76100 Rehovot, Israel
关键词
D O I
10.1126/science.1089167
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:1538 / 1542
页数:5
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