{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T15:12:25Z","timestamp":1761059545415},"reference-count":48,"publisher":"Oxford University Press (OUP)","issue":"16","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,8,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: The analysis of high-throughput molecular data in the context of metabolic pathways is essential to uncover their underlying functional structure. Among different metabolic pathway concepts in systems biology, elementary flux modes (EFMs) hold a predominant place, as they naturally capture the complexity and plasticity of cellular metabolism and go beyond predefined metabolic maps. However, their use to interpret high-throughput data has been limited so far, mainly because their computation in genome-scale metabolic networks has been unfeasible. To face this issue, different optimization-based techniques have been recently introduced and their application to human metabolism is promising.<\/jats:p><jats:p>Results: In this article, we exploit and generalize the K-shortest EFM algorithm to determine a subset of EFMs in a human genome-scale metabolic network. This subset of EFMs involves a wide number of reported human metabolic pathways, as well as potential novel routes, and constitutes a valuable database where high-throughput data can be mapped and contextualized from a metabolic perspective. To illustrate this, we took expression data of 10 healthy human tissues from a previous study and predicted their characteristic EFMs based on enrichment analysis. We used a multivariate hypergeometric test and showed that it leads to more biologically meaningful results than standard hypergeometric. Finally, a biological discussion on the characteristic EFMs obtained in liver is conducted, finding a high level of agreement when compared with the literature.<\/jats:p><jats:p>Contact: \u00a0fplanes@tecnun.es or arubio@ceit.es<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt328","type":"journal-article","created":{"date-parts":[[2013,6,7]],"date-time":"2013-06-07T01:00:10Z","timestamp":1370566810000},"page":"2009-2016","source":"Crossref","is-referenced-by-count":26,"title":["Selection of human tissue-specific elementary flux modes using gene expression data"],"prefix":"10.1093","volume":"29","author":[{"given":"Alberto","family":"Rezola","sequence":"first","affiliation":[{"name":"1 Biomedical Engineering Department, CEIT and Tecnun, University of Navarra, 20009 San Sebastian, Spain, 2Department of Bioinformatics, School of Biology and Pharmacy, Friedrich Schiller University, 07743 Jena, Germany and 3Chemoinformatics and Metabolism Team, EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, CB10 1SD Hinxston, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jon","family":"Pey","sequence":"additional","affiliation":[{"name":"1 Biomedical Engineering Department, CEIT and Tecnun, University of Navarra, 20009 San Sebastian, Spain, 2Department of Bioinformatics, School of Biology and Pharmacy, Friedrich Schiller University, 07743 Jena, Germany and 3Chemoinformatics and Metabolism Team, EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, CB10 1SD Hinxston, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luis F.","family":"de Figueiredo","sequence":"additional","affiliation":[{"name":"1 Biomedical Engineering Department, CEIT and Tecnun, University of Navarra, 20009 San Sebastian, Spain, 2Department of Bioinformatics, School of Biology and Pharmacy, Friedrich Schiller University, 07743 Jena, Germany and 3Chemoinformatics and Metabolism Team, EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, CB10 1SD Hinxston, UK"},{"name":"1 Biomedical Engineering Department, CEIT and Tecnun, University of Navarra, 20009 San Sebastian, Spain, 2Department of Bioinformatics, School of Biology and Pharmacy, Friedrich Schiller University, 07743 Jena, Germany and 3Chemoinformatics and Metabolism Team, EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, CB10 1SD Hinxston, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adam","family":"Podhorski","sequence":"additional","affiliation":[{"name":"1 Biomedical Engineering Department, CEIT and Tecnun, University of Navarra, 20009 San Sebastian, Spain, 2Department of Bioinformatics, School of Biology and Pharmacy, Friedrich Schiller University, 07743 Jena, Germany and 3Chemoinformatics and Metabolism Team, EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, CB10 1SD Hinxston, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Schuster","sequence":"additional","affiliation":[{"name":"1 Biomedical Engineering Department, CEIT and Tecnun, University of Navarra, 20009 San Sebastian, Spain, 2Department of Bioinformatics, School of Biology and Pharmacy, Friedrich Schiller University, 07743 Jena, Germany and 3Chemoinformatics and Metabolism Team, EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, CB10 1SD Hinxston, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Angel","family":"Rubio","sequence":"additional","affiliation":[{"name":"1 Biomedical Engineering Department, CEIT and Tecnun, University of Navarra, 20009 San Sebastian, Spain, 2Department of Bioinformatics, School of Biology and Pharmacy, Friedrich Schiller University, 07743 Jena, Germany and 3Chemoinformatics and Metabolism Team, EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, CB10 1SD Hinxston, 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