An integrated computational environment for elementary modes analysis of biochemical networks

  • Authors:

  • Paulo Maia;Paulo Vilaça;Isabel Rocha;Marcellinus Pont;Jean-François Tomb;Miguel Rocha

  • Affiliations:

  • Department of Biological Engineering, Institute for Biotechnology and Bioengineering, University of Minho, Campus de Gualtar, Braga, Portugal;Department of Biological Engineering, Institute for Biotechnology and Bioengineering, University of Minho, Campus de Gualtar, Braga, Portugal;Department of Biological Engineering, Institute for Biotechnology and Bioengineering, University of Minho, Campus de Gualtar, Braga, Portugal;E.I. DuPont De Nemours & Co., Inc Wilmington, DE 19898, USA;E.I. DuPont De Nemours & Co., Inc Wilmington, DE 19898, USA;Computer Science and Technology Center, Department of Informatics, University of Minho, Campus de Gualtar, Braga, Portugal

  • Venue:
  • International Journal of Data Mining and Bioinformatics
  • Year:
  • 2012

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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 plug-in, running on top of the OptFlux Metabolic Engineering workbench (Rocha et al., 2010), whose aims are to ease the analysis of these results and explore synergies among EFM analysis, phenotype simulation and strain optimisation. Two case studies are shown to illustrate the capabilities of the proposed tool.