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Bioinformatics Advance Access originally published online on June 22, 2007
Bioinformatics 2007 23(16):2139-2146; doi:10.1093/bioinformatics/btm319
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Constraint-based functional similarity of metabolic genes: going beyond network topology{dagger}

Oleg Rokhlenko 1,*, Tomer Shlomi 2, Roded Sharan 2, Eytan Ruppin 2,3 and Ron Y. Pinter 1

1Department of Computer Science, Technion, Haifa 32000, 2School of Computer Science and 3School of Medicine, Tel-Aviv University, Tel-Aviv 69978, Israel

*To whom correspondence should be addressed.


  Abstract

Motivation: Several recent studies attempted to establish measures for the similarity between genes that are based on the topological properties of metabolic networks. However, these approaches offer only a static description of the properties of interest and offer moderate (albeit significant) correlations with pertinent experimental data.

Results: Using a constraint-based large-scale metabolic model, we present two effectively computable measures of functional gene similarity, one based on the response of the metabolic network to gene knockouts and the other based on the metabolic flux activity across a variety of growth media. We applied these measures to 750 genes comprising the metabolic network of the budding yeast. Comparing the in silico computed functional similarities to Gene Ontology (GO) annotations and gene expression data, we show that our computational method captures functional similarities between metabolic genes that go beyond those obtained by the topological analysis of metabolic networks alone, thus revealing dynamic characteristics of gene function. Interestingly, the measure based on the network response to different growth environments markedly outperforms the measure based on its response to gene knockouts, though both have some added synergistic value in depicting the functional relationships between metabolic genes.

Contact: olegro{at}cs.technion.ac.il

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Limsoon Wong

{dagger}A preliminary version of this article appeared as Rokhlenko et al., (2006).

Received on November 21, 2006; revised on June 7, 2007; accepted on June 7, 2007

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[Abstract] [Full Text] [PDF]


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