Evolving networks by merging cliques

Evolving networks by merging cliques.

We propose a model for evolving networks by merging building blocks represented as complete graphs, reminiscent of modules in biological system or communities in sociology. The model shows power-law degree distributions, power-law clustering spectra, and high average clustering coefficients independent of network size. The analytical solutions indicate that a degree exponent is determined by th...

Evolving networks consist of cliques

Many real networks have cliques as their constitutional units. Here we present a family of scale-free network model consist of cliques, which is established by a simple recursive algorithm. We investigate the networks both analytically and numerically. The obtained analytical solution shows that the networks follow a powerlaw degree distribution, with degree exponent continuously tuned between ...

Cooperative Co-Evolving Neural Networks for Robosoccer Simulation

Predicting interactions in protein networks by completing defective cliques

UNLABELLED Datasets obtained by large-scale, high-throughput methods for detecting protein-protein interactions typically suffer from a relatively high level of noise. We describe a novel method for improving the quality of these datasets by predicting missed protein-protein interactions, using only the topology of the protein interaction network observed by the large-scale experiment. The cent...

On Optimal Merging Networks

Kazuyuki Amano? and Akira Maruoka Graduate S hool of Information S ien es, Tohoku University Aoba 05, Aramaki, Sendai 980-8579 JAPAN fama|maruokag e ei.tohoku.a .jp Tel:+81-22-217-7149, Fax:+81-22-263-9414 Abstra t. We prove that Bat her's odd-even (m;n)-merging networks are exa tly optimal for (m;n) = (3; 4k + 2) and (4; 4k + 2) for k 0 in terms of the number of omparators used. For other ases...