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DIA-MCIS: an importance sampling network randomizer for network motif discovery and other topological observables in transcription networks.

TitleDIA-MCIS: an importance sampling network randomizer for network motif discovery and other topological observables in transcription networks.
Publication TypeJournal Article
Year of Publication2007
AuthorsFusco, D, Bassetti, B, Jona, P, Cosentino Lagomarsino, M
JournalBioinformatics
Volume23
Issue24
Pagination3388-90
Date Published2007 Dec 15
ISSN1367-4811
KeywordsAlgorithms, Computer Simulation, Data Interpretation, Statistical, Models, Biological, Models, Statistical, Signal Transduction, Software, Transcription Factors
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

DOI10.1093/bioinformatics/btm454
Alternate JournalBioinformatics
PubMed ID17901083