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PLoS One. 2012;7(2):e31220. doi: 10.1371/journal.pone.0031220. Epub 2012 Feb 21.

A novel framework for the comparative analysis of biological networks.

Author information

1
Joint BSC-IRB Program in Computational Biology, Institute for Research in Biomedicine, Barcelona, Spain.

Abstract

Genome sequencing projects provide nearly complete lists of the individual components present in an organism, but reveal little about how they work together. Follow-up initiatives have deciphered thousands of dynamic and context-dependent interrelationships between gene products that need to be analyzed with novel bioinformatics approaches able to capture their complex emerging properties. Here, we present a novel framework for the alignment and comparative analysis of biological networks of arbitrary topology. Our strategy includes the prediction of likely conserved interactions, based on evolutionary distances, to counter the high number of missing interactions in the current interactome networks, and a fast assessment of the statistical significance of individual alignment solutions, which vastly increases its performance with respect to existing tools. Finally, we illustrate the biological significance of the results through the identification of novel complex components and potential cases of cross-talk between pathways and alternative signaling routes.

PMID:
22363585
PMCID:
PMC3283617
DOI:
10.1371/journal.pone.0031220
[Indexed for MEDLINE]
Free PMC Article

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