Reactienetwerk

Reactienetwerk, often referred to in English as a reaction network, is a formal representation of a set of chemical or biochemical transformations. It consists of a finite set of chemical species and a finite set of reactions that convert one combination of species into another, subject to stoichiometric constraints. The framework provides a compact way to describe how substances are consumed and produced over time.

There are two common viewpoints for describing reactienetwerken. In species-based networks, nodes represent individual chemical species and directed edges denote reactions that convert inputs to outputs. In complex-based networks, nodes correspond to reaction complexes (groups of species) and edges represent the reactions connecting these complexes. The relationships are captured by the stoichiometric matrix, which encodes how each reaction changes the concentrations of all species. Graph representations help illuminate properties such as connectivity, redundancy, and possible pathways.

Dynamics in a reactienetwerk are described by rate laws. Deterministic approaches use ordinary differential equations under assumptions like mass-action kinetics, where reaction rates depend on the concentrations of reactants. Stochastic models, such as the Gillespie algorithm, account for random fluctuations that are important in small systems or low concentrations. The choice of model affects predictions of time evolution, steady states, and response to perturbations.

Applications span chemistry, systems biology, metabolic and signaling networks, pharmacokinetics, and synthetic biology. Analyses focus on steady states, stability, and conservation laws, and leverage structural properties such as network motifs and deficiency. Computational tools like SBML, COPASI, and BioNetGen support the construction, simulation, and analysis of reactienetwerken.