Isotopomer tracer experiments are indispensable for the determination of flux rates in already known pathways as well as for the identification of new pathways. The information gained from such experiments depends on the labeling of the feed tracer metabolite, i.e. the atom positions carrying a label. Here we present an algorithm and a software tool to find an optimal carbon labeling pattern that assures the label to disseminate predominantly into those parts of the network under study. Our implementation is based on carbon fate maps and distinguishes between homotopic and prochiral atoms. In addition, the software can be used to generate carbon transition probability matrices, which can be used for the study of biochemical reaction mechanisms. In this article we present the algorithms and show an application of the software for glycolysis and the TCA cycle.
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