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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.

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