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On an optimal setting of delays for the D-QSSA model reduction method applied to a class of chemical reaction networks
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SYSNO ASEP 0561587 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název On an optimal setting of delays for the D-QSSA model reduction method applied to a class of chemical reaction networks Tvůrce(i) Matonoha, Ctirad (UIVT-O) RID, SAI
Papáček, Štěpán (UTIA-B) ORCID
Lynnyk, Volodymyr (UTIA-B) RID, ORCIDZdroj.dok. Applications of Mathematics. - : Springer - ISSN 0862-7940
Roč. 67, SI 6 (2022), s. 831-857Poč.str. 27 s. Forma vydání Tištěná - P Jazyk dok. eng - angličtina Země vyd. CZ - Česká republika Klíč. slova reaction network ; model reduction ; singular perturbation ; quasi-steady-state approximation ; D-QSSA method ; optimization Obor OECD Pure mathematics CEP GA19-05872S GA ČR - Grantová agentura ČR Způsob publikování Open access s časovým embargem (05.10.2024) Institucionální podpora UIVT-O - RVO:67985807 ; UTIA-B - RVO:67985556 UT WOS 000879014800008 EID SCOPUS 85141158537 DOI 10.21136/AM.2022.0136-21 Anotace We develop and test a relatively simple enhancement of the classical model reduction method applied to a class of chemical networks with mass conservation properties. Both the methods, being (i) the standard quasi-steady-state approximation method, and (ii) the novel so-called delayed quasi-steady-state approximation method, firstly proposed by Vejchodský (2014), are extensively presented. Both theoretical and numerical issues related to the setting of delays are discussed. Namely, for one slightly modified variant of an enzyme-substrate reaction network (Michaelis-Menten kinetics), the comparison of the full non-reduced system behavior with respective variants of reduced model is presented and the results discussed. Finally, some future prospects related to further applications of the delayed quasi-steady-state approximation method are proposed. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2023 Elektronická adresa https://dx.doi.org/10.21136/AM.2022.0136-21
Počet záznamů: 1