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Open Access Method

MetaMerge: scaling up genome-scale metabolic reconstructions with application to Mycobacterium tuberculosis

Leonid Chindelevitch12, Sarah Stanley34, Deborah Hung34, Aviv Regev456 and Bonnie Berger124*

Author affiliations

1 Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA

2 Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar Street, Cambridge, MA 02139, USA

3 Department of Molecular Biology, Massachusetts General Hospital, Simches Research Center, 185 Cambridge Street, Boston, MA 02114, USA

4 Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA

5 Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA

6 Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, MD 20815, USA

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Citation and License

Genome Biology 2012, 13:r6  doi:10.1186/gb-2012-13-1-r6

Published: 31 January 2012

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.