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Bioinformatics Advance Access published online on September 27, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm454
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

DIA-MCIS. An Importance Sampling Network Randomizer for Network Motif Discovery and Other Topological Observables in Transcription Networks.

D. Fusco a,*, B. Bassetti a,b, P. Jona c and M. Cosentino Lagomarsino a,b,d

aUniversità degli Studi di Milano, Dip. Fisica, Via Celoria 16, 20133 Milano, Italy, bI.N.F.N., Milano, Italy, cPolitecnico di Milano, Dip. Fisica, Pza Leonardo Da Vinci 32, 20133 Milano, Italy, dUMR 168 / Institut Curie, 26 rue d’Ulm 75005 Paris, France

*To whom correspondence should be addressed. Diana Fusco, E-mail: diana.fusco{at}studenti.unimi.it


  Abstract

Motivation: Transcription networks, and other directed networks can be characterized by some topological observables (for example network motifs), that require a suitable randomized network ensemble, typically with the same degree sequences of the original ones. The commonly used algorithms sometimes have long convergence times, and sampling problems. We present here an alternative, based on a variant of the importance sampling Monte Carlo developed by Chen et al. (2005).

Availability: The algorithm is available at http://wwwteor.mi.infn.it/bassetti/downloads.html.

Contact: mcl{at}curie.fr, diana.fusco{at}studenti.unimi.it

Associate Editor: Prof. Anna Tramontano

Received on July 24, 2007; revised on August 18, 2007; accepted on August 27, 2007

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