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Metabolic pathway analysis is one of the tools used in biology and medicine in order to understand reaction cycles in living cells. A shortcoming of the approach, however, is that reactions are analysed only at a level corresponding to what is known as the 'collective token view' in Petri nets, i.e., summarising the number of atoms of certain types in a compound, but not keeping track of their identity. In this paper we propose a refinement of pathway analysis based on hypergraph grammars, modelling reactions at a molecular level. We consider as an example the citric acid cycle, a classical, but non-trivial reaction for energy utilisation in living cells. Our approach allows the molecular analysis of the cycle, tracing the flow of individual carbon atoms based on a simulation using the graph transformation tool AGG.

Molecular Analysis of Metabolic Pathway with Graph Transformation