Method

MIRAGE: a functional genomics-based approach for metabolic network model reconstruction and its application to cyanobacteria networks

Edward Vitkin and Tomer Shlomi^*

• * Corresponding author: Tomer Shlomi tomersh@cs.technion.ac.il

Author Affiliations

Department of Computer Science, Technion - Israel Institute of Technology, Haifa 32000, Israel

For all author emails, please log on.

Genome Biology 2012, 13:R111 doi:10.1186/gb-2012-13-11-r111

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Published: 29 November 2012

Abstract

Genome-scale metabolic network reconstructions are considered a key step in quantifying the genotype-phenotype relationship. We present a novel gap-filling approach, MetabolIc Reconstruction via functionAl GEnomics (MIRAGE), which identifies missing network reactions by integrating metabolic flux analysis and functional genomics data. MIRAGE's performance is demonstrated on the reconstruction of metabolic network models of E. coli and Synechocystis sp. and validated via existing networks for these species. Then, it is applied to reconstruct genome-scale metabolic network models for 36 sequenced cyanobacteria amenable for constraint-based modeling analysis and specifically for metabolic engineering. The reconstructed network models are supplied via standard SBML files.