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Bioinformatics Advance Access originally published online on September 27, 2007
Bioinformatics 2007 23(24):3388-3390; 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 1,*, B. Bassetti 1,2, P. Jona 3 and M. Cosentino Lagomarsino 1,2,4

1Università degli Studi di Milano, Dip. Fisica, Via Celoria 16, 20133 Milano, 2I.N.F.N., Milano, 3Politecnico di Milano, Dip. Fisica, Pza Leonardo Da Vinci 32, 20133 Milano, Italy and 4UMR 168/Institut Curie, 26 rue d'Ulm 75005 Paris, France

*To whom correspondence should be addressed.


  Abstract

Motivation: Transcription networks, and other directed networks can be characterized by some topological observables (e.g. 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.).

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

Contact: diana.fusco{at}studenti.unimi.it and marco.cosentino{at}unimi.it

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Anna Tramontano

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

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