Reaction Networks as a Language for Systemic Modeling: Fundamentals and Examples

Abstract

Abstract:The basic processes that bring about living systems are conventionally represented in the framework of chemical reaction networks. Recently, it has been proposed that this framework can be exploited for studying various other phenomena. Reaction networks are specially suited for representing situations where different types of entities interact in contextual ways leading to the emergence of meta-structures. At an abstract level, a reaction network represents a universe whose evolution corresponds to the transformation of collections of entities into other collections of entities. Hence, we propose that systems correspond to the sub-networks that are stable enough to be observed. In this article, we discuss how to use reaction networks for representing systems. Namely, we introduce the different representational levels available (relational, stoichiometric, and kinetic), we show how to identify observable systems in the reaction network, discuss some relevant systemic notions such as context, emergence, and meta-system, and present some examples.

Reaction Networks as a Language for Systemic Modeling: On the Study of Structural Changes

“…The core ideas of this work lie at the stoichiometric level of representation. For a comprehensive introduction to COT, we refer to [6,7].…”

“…This fact was used to propose the reaction network formalism as a language for modeling systems, by noting that the set of organizations of a reaction network corresponds to the observable systems in the reaction network universe [6].…”

“…However, since COT allows for lift information gathered at the stoichiometric level to the kinetic level (at a reasonable computational cost, see Theorem 1 in [6]), we can focus on exploiting stoichiometric properties that provide a better understanding at the kinetic level.…”

“…In what follows, we will advance the structural notions of COT presented in [6]. In particular, we will develop a Theorem that allows for decomposing the inner structure of a system into a collection of dynamically independent self-maintaining sets.…”

“…In [6], we have proposed using reaction networks (RN) as a language for modeling systems. In particular, we showed that, by using Chemical Organization Theory (COT), we can compute the set of possible observable systems from a reaction network universe.…”