Abstract
Elementary Flux Modes (EFMs) have been claimed as one of the most promising approaches for pathway analysis. These are a set of vectors that emerge from the stoichiometric matrix of a biochemical network through the use of convex analysis. The computation of all EFMs of a given network is an NP-hard problem and existing algorithms do not scale well. Moreover, the analysis of results is difficult given the thousands or millions of possible modes generated. In this work, we propose a new plugin, running on top of the OptFlux Metabolic Engineering workbench, whose aims are to ease the analysis of these results and explore synergies among EFM analysis, phenotype simulation and strain optimization.
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Maia, P., Pont, M., Tomb, JF., Rocha, I., Rocha, M. (2010). Enhancing Elementary Flux Modes Analysis Using Filtering Techniques in an Integrated Environment. In: Rocha, M.P., Riverola, F.F., Shatkay, H., Corchado, J.M. (eds) Advances in Bioinformatics. Advances in Intelligent and Soft Computing, vol 74. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13214-8_28
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DOI: https://doi.org/10.1007/978-3-642-13214-8_28
Publisher Name: Springer, Berlin, Heidelberg
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