title: MetaMerge: scaling up genome-scale metabolic reconstructions with application to Mycobacterium tuberculosis.
abstract: Reconstructed models of metabolic networks are widely used for studying metabolism in various organisms. Many different reconstructions of the same organism often exist concurrently, forcing researchers to choose one of them at the exclusion of the others. We describe MetaMerge, an algorithm for semi-automatically reconciling a pair of existing metabolic network reconstructions into a single metabolic network model. We use MetaMerge to combine two published metabolic networks for Mycobacterium tuberculosis into a single network, which allows many reactions that could not be active in the individual models to become active, and predicts essential genes with a higher positive predictive value.
authors.affiliation: Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
authors.forename: Leonid
authors.initials: L
authors.lastname: Chindelevitch
authors.forename: Sarah
authors.initials: S
authors.lastname: Stanley
authors.forename: Deborah
authors.initials: D
authors.lastname: Hung
authors.forename: Aviv
authors.initials: A
authors.lastname: Regev
authors.forename: Bonnie
authors.initials: B
authors.lastname: Berger
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D016680:Genome, Bacterial; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008954:Models, Biological; D009169:Mycobacterium tuberculosis / Q000235:genetics / Q000378:metabolism*