Analysis of a Model Reduction Method (D-QSSA) applied to a Class of Biochemical Networks

0546360 - ÚTIA 2022 RIV NL eng C - Conference Paper (international conference)
Papáček, Štěpán - Rehák, Branislav - Lynnyk, Volodymyr - Lynnyk, Anna
Analysis of a Model Reduction Method (D-QSSA) applied to a Class of Biochemical Networks.
IFAC-PapersOnLine.Volume 54, Issue 15 - 11th IFAC Symposium on Biological and Medical Systems BMS 2021. Amsterdam: Elsevier, 2021, s. 568-573. ISSN 2405-8963.
[Biological and Medical Systems - 11th IFAC Symposium BMS 2021™, Ghent, Belgium. Ghent (BE), 19.09.2021-22.09.2021]
R&D Projects: GA ČR(CZ) GA19-05872S
Institutional support: RVO:67985556
Keywords : Biochemical reaction network * Model reduction * D-QSSA method * Model parameter estimation
OECD category: Applied mathematics
https://www.sciencedirect.com/science/article/pii/S2405896321017225

This paper is aimed to develop and test one novel and unexplored enhancement of the classical model reduction method applied to a class of biochemical networks. Both methods, being (i) the standard quasi-steady-state approximation (QSSA), and (ii) the so-called delayed-QSSA methods are extensively presented. Specially, the numerical issues related to the setting of constant delays are discussed. Finally, for one slightly modi ed version of an enzymesubstrate reaction network (Michaelis-Menten kinetics), the comparison of the full non-reduced system behavior with respective variants of reduced model is presented and future prospects are
proposed.
Permanent Link: http://hdl.handle.net/11104/0322887