Convex representation of metabolic networks with Michaelis-Menten kinetics - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Journal Articles Bulletin of Mathematical Biology Year : 2024

Convex representation of metabolic networks with Michaelis-Menten kinetics

Abstract

Polyhedral models of metabolic networks are computationally tractable and can predict some cellular functions. A longstanding challenge is incorporating metabolites without losing tractability. In this paper, we do so using a new second-order cone representation of the Michaelis-Menten kinetics. The resulting model consists of linear stoichiometric constraints alongside second-order cone constraints that couple the reaction fluxes to metabolite concentrations. We formulate several new problems around this model: conic flux balance analysis, which augments flux balance analysis with metabolite concentrations; dynamic conic flux balance analysis; and finding minimal cut sets of networks with both reactions and metabolites. Solving these problems yields information about both fluxes and metabolite concentrations. They are second-order cone or mixed-integer second-order cone programs, which, while not as tractable as their linear counterparts, can nonetheless be solved at practical scales using existing software.
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Dates and versions

hal-04536948 , version 1 (08-04-2024)

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Josh A Taylor, Alain Rapaport, Denis Dochain. Convex representation of metabolic networks with Michaelis-Menten kinetics. Bulletin of Mathematical Biology, 2024, 86 (65), ⟨10.1007/s11538-024-01293-1⟩. ⟨hal-04536948⟩
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