caa a22 4500 445842997 CHVBK 20180317145350.0 cr unu---uuuuu 170323e20110601xx s 000 0 eng 10.1007/s11047-009-9163-7 doi (NATIONALLICENCE)springer-10.1007/s11047-009-9163-7 Angeli David Dipartimento di Sistemi e Informatica, University of Florence, Florence, Italy aut Boundedness analysis for open Chemical Reaction Networks with mass-action kinetics [Elektronische Daten] [David Angeli] This paper describes the working principles of an algorithm for boundedness analysis of open Chemical Reaction Networks endowed with mass-action kinetics. Such models can be thought of both as a special class of compartmental systems or a particular type of continuous Petri Nets, in which the firing rates of transitions are not constant or preassigned, but expressed as a function of the continuous marking of the network (function which in chemistry is referred to as the "kinetics”). The algorithm can be applied to a broad class of such open networks, and returns, as an outcome, a classification of the possible dynamical behaviors that are compatible with the network structure, by classifying each variable either as bounded, converging to 0 or diverging to ∞. This can be viewed as a qualitative study of Input-Output Stability for chemical networks, or more precisely, as a classification of its possible I-O instability patterns. Our goal is to analyze the system irrespectively of values of kinetic parameters. More precisely, we attempt to analyze it simultaneously for all possible values. Remarkably, tests on non-trivial examples (one of which is discussed in this paper) showed that, as the kinetic constants of the network are varied, all the compatible behaviors could be observed in simulations. Finally, we discuss and illustrate how the results relate to previous works on the qualitative dynamics of closed reaction networks. Springer Science+Business Media B.V., 2009 Chemical Reaction Networks nationallicence Continuous Petri Nets nationallicence Mass-action kinetics nationallicence Input-output stability nationallicence Open systems nationallicence Natural Computing Springer Netherlands 10/2(2011-06-01), 751-774 1567-7818 10:2<751 2011 10 11047 https://doi.org/10.1007/s11047-009-9163-7 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11047-009-9163-7 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Angeli David Dipartimento di Sistemi e Informatica, University of Florence, Florence, Italy aut NATIONALLICENCE 773 0- Natural Computing Springer Netherlands 10/2(2011-06-01), 751-774 1567-7818 10:2<751 2011 10 11047 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer