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00925njm 22002777a 4500 dc Alberich, Ricardo author Castro, Jose A author Llabres, Merce author Palmer-Rodriguez, Pere author 2017-05-11 In this paper we propose a new methodology for the analysis of metabolic networks. We use the notion of strongly connected components of a graph, called in this context metabolic building blocks. Every strongly connected component is contracted to a single node in such a way that the resulting graph is a directed acyclic graph, called a metabolic DAG, with a considerably reduced number of nodes. The property of being a directed acyclic graph brings out a background graph topology that reveals the connectivity of the metabolic network, as well as bridges, isolated nodes and cut nodes. Altogether, it becomes a key information for the discovery of functional metabolic relations. Our methodology has been applied to the glycolysis and the purine metabolic pathways for all organisms in the KEGG database, although it is general enough to work on any database. As expected, using the metabolic DAGs formalism, a considerable reduction on the size of the metabolic networks has been obtained, specially in the case of the purine pathway due to its relative larger size. As a proof of concept, from the information captured by a metabolic DAG and its corresponding metabolic building blocks, we obtain the core of the glycolysis pathway and the core of the purine metabolism pathway and detect some essential metabolic building blocks that reveal the key reactions in both pathways. Finally, the application of our methodology to the glycolysis pathway and the purine metabolism pathway reproduce the tree of life for the whole set of the organisms represented in the KEGG database which supports the utility of this research. Alberich Marti R, Castro JA, Llabres Segura M, Palmer-Rodriguez P. Metabolomics analysis: Finding out metabolic building blocks. PLoS One. 2017 May 11;12(5):e0177031. 10.1371/journal.pone.0177031 1932-6203 PloS One http://hdl.handle.net/20.500.13003/9832 28493998 L616080565 2-s2.0-85019055878 http://hdl.handle.net/20.500.12105/20430 401314300052 Metabolomics analysis: Finding out metabolic building blocks