{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,2,2]],"date-time":"2023-02-02T00:40:08Z","timestamp":1675298408768},"reference-count":52,"publisher":"Oxford University Press (OUP)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,2,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation : Genome-scale metabolic network reconstructions have been established as a powerful tool for the prediction of cellular phenotypes and metabolic capabilities of organisms. In recent years, the number of network reconstructions has been constantly increasing, mostly because of the availability of novel (semi-)automated procedures, which enabled the reconstruction of metabolic models based on individual genomes and their annotation. The resulting models are widely used in numerous applications. However, the accuracy and predictive power of network reconstructions are commonly limited by inherent inconsistencies and gaps.<\/jats:p>\n               <jats:p>Results : Here we present a novel method to validate metabolic network reconstructions based on the concept of autocatalytic sets. Autocatalytic sets correspond to collections of metabolites that, besides enzymes and a growth medium, are required to produce all biomass components in a metabolic model. These autocatalytic sets are well-conserved across all domains of life, and their identification in specific genome-scale reconstructions allows us to draw conclusions about potential inconsistencies in these models. The method is capable of detecting inconsistencies, which are neglected by other gap-finding methods. We tested our method on the Model SEED, which is the largest repository for automatically generated genome-scale network reconstructions. In this way, we were able to identify a significant number of missing pathways in several of these reconstructions. Hence, the method we report represents a powerful tool to identify inconsistencies in large-scale metabolic networks.<\/jats:p>\n               <jats:p>Availability and implementation : The method is available as source code on http:\/\/users.minet.uni-jena.de\/\u223cm3kach\/ASBIG\/ASBIG.zip .<\/jats:p>\n               <jats:p>Contact : christoph.kaleta@uni-jena.de<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu658","type":"journal-article","created":{"date-parts":[[2014,10,7]],"date-time":"2014-10-07T04:41:50Z","timestamp":1412656910000},"page":"373-381","source":"Crossref","is-referenced-by-count":2,"title":["Computing autocatalytic sets to unravel inconsistencies in metabolic network reconstructions"],"prefix":"10.1093","volume":"31","author":[{"given":"Ralf","family":"Schmidt","sequence":"first","affiliation":[{"name":"1 Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, 2 Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, 3 Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Kn\u00f6ll Institute, 07745 Jena and 4 Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Silvio","family":"Waschina","sequence":"additional","affiliation":[{"name":"1 Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, 2 Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, 3 Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Kn\u00f6ll Institute, 07745 Jena and 4 Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark"},{"name":"1 Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, 2 Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, 3 Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Kn\u00f6ll Institute, 07745 Jena and 4 Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniela","family":"Boettger-Schmidt","sequence":"additional","affiliation":[{"name":"1 Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, 2 Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, 3 Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Kn\u00f6ll Institute, 07745 Jena and 4 Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christian","family":"Kost","sequence":"additional","affiliation":[{"name":"1 Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, 2 Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, 3 Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Kn\u00f6ll Institute, 07745 Jena and 4 Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christoph","family":"Kaleta","sequence":"additional","affiliation":[{"name":"1 Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, 2 Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, 3 Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Kn\u00f6ll Institute, 07745 Jena and 4 Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark"},{"name":"1 Research Group Theoretical Systems Biology, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, 07743 Jena, 2 Department of Bioorganic Chemistry, Experimental Ecology and Evolution Research Group, Max Planck Institute for Chemical Ecology, 07745 Jena, 3 Department of Biomolecular Chemistry, Leibniz Institute for Natural Product Research and Infection Biology - Hans Kn\u00f6ll Institute, 07745 Jena and 4 Department of Computational Biology, Institute for Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2014,10,5]]},"reference":[{"key":"2023020116161869700_btu658-B1","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1007\/s11103-008-9415-4","article-title":"Insights into corn genes derived from large-scale cDNA sequencing","volume":"69","author":"Alexandrov","year":"2009","journal-title":"Plant Mol. 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Identification of a calmodulin binding isoform \n              Plant","volume":"135","author":"Turner","year":"2004","journal-title":"Physiol."},{"key":"2023020116161869700_btu658-B45","doi-asserted-by":"crossref","first-page":"3724","DOI":"10.1128\/aem.60.10.3724-3731.1994","article-title":"Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type \n              Escherichia coli\n               W3110","volume":"60","author":"Varma","year":"1994","journal-title":"Appl. Environ. Microbiol."},{"key":"2023020116161869700_btu658-B46","doi-asserted-by":"crossref","first-page":"3680","DOI":"10.1093\/bioinformatics\/bth422","article-title":"The jigcell model builder and run manager","volume":"20","author":"Vass","year":"2004","journal-title":"Bioinformatics"},{"key":"2023020116161869700_btu658-B47","doi-asserted-by":"crossref","first-page":"5978","DOI":"10.1128\/JB.186.18.5978-5987.2004","article-title":"The architecture of the murein (peptidoglycan) in Gram-negative bacteria: vertical scaffold or horizontal layer(s)?","volume":"186","author":"Vollmer","year":"2004","journal-title":"J. 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Biotechnol."},{"key":"2023020116161869700_btu658-B50","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1038\/msb.2011.46","article-title":"Optimal regulatory strategies for metabolic pathways in \n              Escherichia coli\n               depending on protein costs","volume":"7","author":"Wessely","year":"2011","journal-title":"Mol. Syst. 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