{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T14:37:09Z","timestamp":1778942229055,"version":"3.51.4"},"reference-count":26,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":480,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,6,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Structural kinetic modelling (SKM) is a framework to analyse whether a metabolic steady state remains stable under perturbation, without requiring detailed knowledge about individual rate equations. It provides a representation of the system\u2019s Jacobian matrix that depends solely on the network structure, steady state measurements, and the elasticities at the steady state. For a measured steady state, stability criteria can be derived by generating a large number of SKMs with randomly sampled elasticities and evaluating the resulting Jacobian matrices. The elasticity space can be analysed statistically in order to detect network positions that contribute significantly to the perturbation response. Here, we extend this approach by examining the kinetic feasibility of the elasticity combinations created during Monte Carlo sampling.<\/jats:p>\n               <jats:p>Results: Using a set of small example systems, we show that the majority of sampled SKMs would yield negative kinetic parameters if they were translated back into kinetic models. To overcome this problem, a simple criterion is formulated that mitigates such infeasible models. After evaluating the small example pathways, the methodology was used to study two steady states of the neuronal TCA cycle and the intrinsic mechanisms responsible for their stability or instability. The findings of the statistical elasticity analysis confirm that several elasticities are jointly coordinated to control stability and that the main source for potential instabilities are mutations in the enzyme alpha-ketoglutarate dehydrogenase.<\/jats:p>\n               <jats:p>Contact: \u00a0dorothee.childs@embl.de<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btv243","type":"journal-article","created":{"date-parts":[[2015,6,13]],"date-time":"2015-06-13T17:12:36Z","timestamp":1434215556000},"page":"i214-i220","source":"Crossref","is-referenced-by-count":5,"title":["Refined elasticity sampling for Monte Carlo-based identification of stabilizing network patterns"],"prefix":"10.1093","volume":"31","author":[{"given":"Dorothee","family":"Childs","sequence":"first","affiliation":[{"name":"1 Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany, 2Bioinformatics Group, University of Potsdam and Max-Planck Institute for Molecular Plant Physiology, Potsdam, Germany and 3Computational Systems Biology Group, School of Engineering and Science, Jacobs University Bremen, Bremen, Germany"},{"name":"1 Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany, 2Bioinformatics Group, University of Potsdam and Max-Planck Institute for Molecular Plant Physiology, Potsdam, Germany and 3Computational Systems Biology Group, School of Engineering and Science, Jacobs University Bremen, Bremen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sergio","family":"Grimbs","sequence":"additional","affiliation":[{"name":"1 Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany, 2Bioinformatics Group, University of Potsdam and Max-Planck Institute for Molecular Plant Physiology, Potsdam, Germany and 3Computational Systems Biology Group, School of Engineering and Science, Jacobs University Bremen, Bremen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joachim","family":"Selbig","sequence":"additional","affiliation":[{"name":"1 Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany, 2Bioinformatics Group, University of Potsdam and Max-Planck Institute for Molecular Plant Physiology, Potsdam, Germany and 3Computational Systems Biology Group, School of Engineering and Science, Jacobs University Bremen, Bremen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2015,6,10]]},"reference":[{"key":"2023020115421812100_btv243-B1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2012\/757594","article-title":"Kinetic modeling of the mitochondrial energy metabolism of neuronal cells: the impact of reduced \u03b1-Ketoglutarate Dehydrogenase activities on ATP production and generation of reactive oxygen species","volume":"2012","author":"Berndt","year":"2012","journal-title":"Int. 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