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Structural kinetic modeling of metabolic networks

  • To develop and investigate detailed mathematical models of metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, kinetic modeling is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a quantitative account of the dynamical capabilities of a metabolic system, without requiring any explicit information about the functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a statistical exploration of the comprehensive parameter space. The method is exemplified on two paradigmatic metabolic systems: theTo develop and investigate detailed mathematical models of metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, kinetic modeling is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a quantitative account of the dynamical capabilities of a metabolic system, without requiring any explicit information about the functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a statistical exploration of the comprehensive parameter space. The method is exemplified on two paradigmatic metabolic systems: the glycolytic pathway of yeast and a realistic-scale representation of the photosynthetic Calvin cycle.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Ralf SteuerORCiD, Thilo GrossORCiDGND, Joachim SelbigGND, Bernd BlasiusORCiDGND
DOI:https://doi.org/10.1073/pnas.0600013103
ISSN:0027-8424
ISSN:1091-6490
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/16880395
Titel des übergeordneten Werks (Englisch):Proceedings of the National Academy of Sciences of the United States of America
Verlag:National Academy of Sciences
Verlagsort:Washington
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:08.08.2006
Erscheinungsjahr:2006
Datum der Freischaltung:24.06.2020
Freies Schlagwort / Tag:biological robustness; computational biochemistry; metabolic regulation; metabolomics; systems biology
Band:103
Ausgabe:32
Seitenanzahl:6
Erste Seite:11868
Letzte Seite:11873
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie
Peer Review:Referiert
Publikationsweg:Open Access
Open Access / Bronze Open-Access
Name der Einrichtung zum Zeitpunkt der Publikation:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik
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