0546360 20250121152513.020211008235959.9 000714393600097 10.1016/j.ifacol.2021.10.317 Analysis of a Model Reduction Method (D-QSSA) applied to a Class of Biochemical Networks 6 s. P cav_un_epca*05476162405-8963IFAC-PapersOnLine.Volume 54, Issue 15 - 11th IFAC Symposium on Biological and Medical Systems BMS 2021568-573AmsterdamElsevier2021 Biochemical reaction network Model reduction D-QSSA method Model parameter estimation cav_un_auth*0404313 Papáček Štěpán UTIA-B Teorie řízení Department of Control Theory TŘ TR CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0216347 Rehák Branislav UTIA-B Teorie řízení Department of Control Theory TŘ TR Department of Control Theory Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0215855 Lynnyk Volodymyr UTIA-B Teorie řízení Department of Control Theory TŘ TR Department of Control Theory Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0414979 Lynnyk Anna UTIA-B Teorie řízení Department of Control Theory TŘ TR CZ Ústav teorie informace a automatizace AV ČR, v. v. i. konferenční příspěvek https://www.sciencedirect.com/science/article/pii/S2405896321017225 374 KB GA19-05872S GA ČR CZ cav_un_auth*0376352 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. cav_un_auth*0414980 Biological and Medical Systems - 11th IFAC Symposium BMS 2021™, Ghent, Belgium 20210919 20210922 Ghent BE BC 10000 10100 10102 2022 PR RVO:67985556 http://hdl.handle.net/11104/0322887 S 20210722 99 0.332 18.32 1.1 7175 Q2 Q4 2021 SCOPUS PUBMED 000714393600097 WOS konferenční příspěvek 374 KB cav_un_epca*0547616 IFAC-PapersOnLine.Volume 54, Issue 15 - 11th IFAC Symposium on Biological and Medical Systems BMS 2021 Elsevier 2021 Amsterdam 568 573 2405-8963