Convex representation of metabolic networks with Michaelis-Menten kinetics
(2024) Bulletin of Mathematical Biology — Vol. 86, n° 65 (2024)
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- Authors
Dochain, Denis 
- 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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Citations
Joshua Taylor, Alain Rapaport, & Dochain, D. (2024). Convex representation of metabolic networks with Michaelis-Menten kinetics. Bulletin of Mathematical Biology, 86(65). https://hdl.handle.net/2078.5/218073 (Original work published 2024)