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Journal of Computational Biology
Using Atom Mapping Rules for an Improved Detection of Relevant Routes in Weighted Metabolic Networks

To cite this article:
Torsten Blum, Oliver Kohlbacher. Journal of Computational Biology. July/August 2008, 15(6): 565-576. doi:10.1089/cmb.2008.0044.

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Torsten Blum 
Division for Simulation of Biological Systems, University of Tübingen, Tübingen, Germany.
Oliver Kohlbacher 
Division for Simulation of Biological Systems, University of Tübingen, Tübingen, Germany.

Computational analysis of pathways in metabolic networks has numerous applications in systems biology. While graph theory–based approaches have been presented that find biotransformation routes from one metabolite to another in these networks, most of these approaches suffer from finding too many routes, most of which are biologically infeasible or meaningless. We present a novel approach for finding relevant routes based on atom mapping rules (describing which educt atoms are mapped onto which product atoms in a chemical reaction). This leads to a reformulation of the problem as a lightest path search in a degree-weighted metabolic network. The key component of the approach is a new method of computing optimal atom mapping rules.

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