BioSystems 75 (2004) 29–41 Discrete event, multi-level simulation of metabolite channeling Daniela Degenring, Mathias Röhl, Adelinde M. Uhrmacher ∗ Department of Computer Science, University of Rostock, Rostock D-18051, Germany Abstract Typically differential equations are employed to simulate cellular dynamics. To develop a valid continuous model based on differential equations requires accurate parameter estimations; an accuracy which is often difficult to achieve, due to the lack of data. In addition, processes in metabolic pathways, e.g. metabolite channeling, seem to be of a rather qualitative and discrete nature. With respect to the available data and to the perception of the underlying system, a discrete rather than a continuous approach to modeling and simulation seems more adequate. A discrete approach does not necessarily imply a more abstract view on the system. If we move from macro to micro and multi-level modeling, aspects of subsystems and their interactions, which have been only implicitly represented, become an explicit part of the model. To start exploring discrete event phenomena within metabolite channeling we choose the tryptophan synthase. Based on a continuous macro model, a discrete event, multi-level model is developed which allows us to analyze the interrelation between structural and functional characteristics of the enzymes. © 2004 Elsevier Ireland Ltd. All rights reserved. Keywords: Discrete event simulation; Multi-level simulation; Metabolite channeling; Tryptophan synthase 1. Introduction The most common modeling and simulation ap- proach in natural and engineering sciences is to use differential equations. Researchers interested in the dynamics of cellular systems feel comfortable with the well known formalism. Difficulties of determin- ing suitable numerical algorithms are solved transpar- ently to the user by commercial systems. Simulation tools like Gepasi (Mendes, 1993), PathwayPrism TM (Natarajan et al., 2001) support a comfortable mod- eling of cellular systems and a numerical execution of models that describe regulation in great detail. A problem of modeling with differential equations is that systems proceed not necessarily continuously and de- terministically. The latter can be addressed by stochas- ∗ Corresponding author. E-mail address: lin@informatik.uni-rostock.de (A.M. Uhrmacher). tic differential equations (McAdams and Arkin, 1997), whereas the former calls for qualitative and discrete modeling formalisms. The variety of formalisms that are employed for modeling and simulating cellular systems, e.g. qualita- tive differential equations, boolean networks (de Jong, 2000), Petri Nets (Chen et al., 2001) and the -calculus (Priami et al., 2001), gives evidence not only of the wish to test formalisms in a new application area but also of the importance of diversity: one formalism will hardly suffice to describe and analyze all phenomena of cellular systems in a natural manner. Typical crite- ria to help us structuring the space of different mod- eling formalisms, see for example Uhrmacher (1995), are whether parameters and variables are qualitatively or/and quantitatively scaled, whether the time scale is of a continuous or discrete nature and whether stochas- tic aspects are supported. Modeling with differential equations presupposes a continuous state space and a continuous time scale. In contrast, discrete event ap- 0303-2647/$ – see front matter © 2004 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.biosystems.2004.03.008