Parameter Identification in Metabolic Reaction Networks by Means of Multiple Steady-State Measurements

Autor: Giovanni Palombo, Alessandro Borri, Federico Papa, Marco Papi, Pasquale Palumbo
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Symmetry, Vol 15, Iss 2, p 368 (2023)
Druh dokumentu: article
ISSN: 2073-8994
DOI: 10.3390/sym15020368
Popis: In this work, we investigate some theoretical aspects related to the estimation approach proposed by Liebermeister and Klipp, 2006, in which general rate laws, derived from standardized enzymatic mechanisms, are exploited to kinetically describe the fluxes of a metabolic reaction network, and multiple metabolic steady-state measurements are exploited to estimate the unknown kinetic parameters. Further mathematical details are deeply investigated, and necessary conditions on the amount of information required to solve the identification problem are given. Moreover, theoretical results for the parameter identifiability are provided, and symmetrical and modular properties of the proposed approach are highlighted when the global identification problem is decoupled into smaller and simpler identification problems related to the single reactions of the network. Among the advantages of the proposed innovative approach are (i) non-restrictive conditions to guarantee the solvability of the parameter estimation problem, (ii) the unburden of the usual computational complexity for such identification problems, and (iii) the ease of obtaining the required number of measurements, which are actually steady-state data, experimentally easier to obtain with respect to the time-dependent ones. A simple example concludes the paper, highlighting the mentioned advantages of the method and the implementation of the related theoretical result.
Databáze: Directory of Open Access Journals
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