Reakcionet

Reakcionet is a term used in discussions of reaction networks to describe the interconnected set of chemical reactions that govern how species transform within a system. It refers to both the structural arrangement of reactions and the dynamic processes that determine their rates. The concept is widely applied in chemistry, systems biology, and chemical engineering to study how complex behavior emerges from many interacting reactions.

Practically, a reakcionet is often represented as a directed graph: nodes correspond to chemical species, and edges denote elementary reactions equipped with stoichiometric coefficients and rate laws. Deterministic models use ordinary differential equations based on mass-action or generalized kinetics to track concentrations over time; stochastic models are used when species exist in small numbers.

Analysis uses network-theory metrics to identify key species or reactions, including centrality, connectivity, and motifs. Flux analysis, sensitivity analysis, and stability studies help assess how changes in parameters or network structure affect outcomes. Computational tools simulate the system and visualize pathways.

Applications range from metabolic engineering and drug metabolism to environmental chemistry and combustion. By examining the structure of a reakcionet, researchers can identify bottlenecks, design more efficient pathways, or predict system responses to perturbations such as inhibitors or changes in temperature.

Origin and usage vary by region and discipline; the term is closely related to reaction network theory and chemical reaction network theory, and is supported by software such as COPASI, CellDesigner, and BNGL tools.