Steady states and stability in metabolic networks without regulation

Иванов, О.П.; Schaft, A.J. van der; Weissing, Franz J.

doi:10.1016/j.jtbi.2016.02.031

Cited by 4 publications

(6 citation statements)

References 27 publications

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“…This approach to chemical reaction network theory was further developed by Sontag [16], Angeli [17], and van der Schaft et al [18,19,20]. General results on stability of both closed and open systems of chemical reactions have been derived and applied to reveal dynamic features of complex (bio)chemical networks [21], dissipation in noisy chemical networks Polettini et al [22], metabolic networks [23] and multistability in interferon signalling Otero-Muras et al [24].…”

Section: Conclusion 1 Introductionmentioning

confidence: 99%

Bond Graph Representation of Chemical Reaction Networks

Gawthrop

Crampin

2018

IEEE Trans.on Nanobioscience

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The Bond Graph approach and the Chemical Reaction Network approach to modelling biomolecular systems developed independently. This paper brings together the two approaches by providing a bond graph interpretation of the chemical reaction network concept of complexes. Both closed and open systems are discussed.The method is illustrated using a simple enzyme-catalysed reaction and a transmembrane transporter.

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Section: Conclusion 1 Introductionmentioning

confidence: 99%

Bond Graph Representation of Chemical Reaction Networks

Gawthrop

Crampin

2018

IEEE Trans.on Nanobioscience

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“…In other words, in spite of the presence of modest disturbances an unstable network may reach physiological constraints and collapse. Several authors have addressed the analysis of biological systems of small to moderate size [1][2][3][4][5]. Diaz Ricci [1] studies local stability of Correspondence: Prof. M. Soledad Diaz (sdiaz@plapiqui.edu.ar).…”

Section: Introductionmentioning

confidence: 99%

“…The authors construct bifurcation diagrams that show that the central carbon metabolism can exhibit oscillatory behavior for certain parameter values. Ivanov et al [4] study the properties of steady states in metabolic networks with monotonic kinetics, in relation to their stoichiometry and the number of metabolites that participate in every reaction. The study is based on the investigation of the Jacobian matrix properties.…”

Section: Introductionmentioning

confidence: 99%

“…In other words, in spite of the presence of modest disturbances an unstable network may reach physiological constraints and collapse. Several authors have addressed the analysis of biological systems of small to moderate size . Diaz Ricci studies local stability of phosphofructokinase (PFK) enzyme through the analysis of the eigenvalues of a kinetic model that comprises mass balances for its substrate and product.…”

Section: Introductionmentioning

confidence: 99%

“…Ivanov et al. study the properties of steady states in metabolic networks with monotonic kinetics, in relation to their stoichiometry and the number of metabolites that participate in every reaction. The study is based on the investigation of the Jacobian matrix properties.…”

Section: Introductionmentioning

confidence: 99%

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Design of stable metabolic networks

Maggio

Blanco

Bandoni

et al. 2017

Engineering in Life Sciences

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In this work, we propose eigenvalue optimization combined with Lyapunov theory concepts to ensure stability of the Embden-Meyerhof-Parnas pathway, the pentosephosphate pathway, the phosphotransferase system and fermentation reactions of Escherichia coli. We address the design of a metabolic network for the maximization of different metabolite production rates. The first case study focuses on serine production, based on a model that consists of 18 differential equations corresponding to dynamic mass balances for extracellular glucose and intracellular metabolites, and thirty kinetic rate expressions. A second case study addresses the design problem to maximize ethanol production, based on a dynamic model that involves mass balances for 25 metabolites and 38 kinetic rate equations. The nonlinear optimization problem including stability constraints has been solved with reduced space Successive Quadratic Programming techniques. Numerical results provide useful insights on the stability properties of the studied kinetic models.

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A Practical Guide to Integrating Multimodal Machine Learning and Metabolic Modeling

Vijayakumar

Magazzù

Moon

et al. 2022

Methods in Molecular Biology

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Complex, distributed and dynamic sets of clinical biomedical data are collectively referred to as multimodal clinical data. In order to accommodate the volume and heterogeneity of such diverse data types and aid in their interpretation when they are combined with a multi-scale predictive model, machine learning is a useful tool that can be wielded to deconstruct biological complexity and extract relevant outputs. Additionally, genome-scale metabolic models (GSMMs) are one of the main frameworks striving to bridge the gap between genotype and phenotype by incorporating prior biological knowledge into mechanistic models. Consequently, the utilization of GSMMs as a foundation for the integration of multi-omic data

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Steady states and stability in metabolic networks without regulation

Cited by 4 publications

References 27 publications

Bond Graph Representation of Chemical Reaction Networks

Bond Graph Representation of Chemical Reaction Networks

Design of stable metabolic networks

A Practical Guide to Integrating Multimodal Machine Learning and Metabolic Modeling

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