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---------- Forwarded message ----------
Date: Tue, 01 Jun 2004 15:14:10 +0200
From: BMS-RC33 <[log in to unmask]>
To: [log in to unmask]
Subject: Article - Complex Systems: On Superfamilies of Networks  (Science,

Thanks to Science Week, May 21, 2004


The following points are made by R. Milo et al (Science 2004 303:
1538) Science

1) Many networks in nature share global properties (1,2). Their
degree sequences (the number of edges per node) often follow a
long-tailed distribution in which some nodes are much more
connected than the average (3). In addition, natural networks
often show the small-world property of short paths between nodes
and highly clustered connections (1,2,4). Despite these global
similarities, networks from different fields can have very
different local structure (5). It was recently found that
networks display certain patterns, termed "network motifs", at
much higher frequency than expected in randomized networks. In
biological networks, these motifs were suggested to be recurring
circuit elements that carry out key information-processing tasks.

2) To understand the design principles of complex networks, it is
important to compare the local structure of networks from
different fields. The main difficulty is that these networks can
be of vastly different sizes [for example, World Wide Web (WWW)
hyperlink networks with millions of nodes and social networks
with tens of nodes] and degree sequences. Here, the authors
present an approach for comparing network local structure, based
on the significance profile (SP). To calculate the SP of a
network, the network is compared to an ensemble of randomized
networks with the same degree sequence. The comparison to
randomized networks compensates for effects due to network size
and degree sequence.

3) In summary: Complex biological, technological, and
sociological networks can be of very different sizes and
connectivities, making it difficult to compare their structures.
The authors 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. The authors 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.

References (abridged):

1. S. H. Strogatz, Nature 410, 268 (2001)

2. M. Newman, SIAM Rev. 45, 167 (2003)

3. A. L. Barabasi, R. Albert, Science 286, 509 (1999)

4. D. J. Watts, S. H. Strogatz, Nature 393, 440 (1998)

5. S. Maslov, K. Sneppen, Science 296, 910 (2002)

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