Literature DB >> 23788432

Elementary flux modes in a nutshell: properties, calculation and applications.

Jürgen Zanghellini1, David E Ruckerbauer, Michael Hanscho, Christian Jungreuthmayer.   

Abstract

Elementary flux mode (EFM) analysis allows the unbiased decomposition of a metabolic network into minimal functional units, making it a powerful tool for metabolic engineering. While the use of EFM analysis (EFMA) is still limited by the size of the models it can handle, EFMA has been successfully applied to solve real-world metabolic engineering problems. Here we provide a user-oriented introduction to EFMA, provide examples of recent applications, analyze current research strategies to overcome the computational restrictions and give an overview over current approaches, which aim to identify and calculate only biologically relevant EFMs.
Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Keywords:  Computational methods; Metabolic engineering; Metabolic pathway analysis; Minimal cut set; Strain optimization

Mesh：

Year:  2013        PMID： 23788432     DOI： 10.1002/biot.201200269

Source DB:  PubMed          Journal:  Biotechnol J        ISSN： 1860-6768            Impact factor:   4.677


  23 in total

1.  A portable structural analysis library for reaction networks.

Authors:  Yosef Bedaso; Frank T Bergmann; Kiri Choi; Kyle Medley; Herbert M Sauro
Journal:  Biosystems       Date:  2018-05-30       Impact factor: 1.973

2.  Elucidating Plant-Microbe-Environment Interactions Through Omics-Enabled Metabolic Modelling Using Synthetic Communities.

Authors:  Ashley E Beck; Manuel Kleiner; Anna-Katharina Garrell
Journal:  Front Plant Sci       Date:  2022-06-20       Impact factor: 6.627

3.  Metabolomics integrated elementary flux mode analysis in large metabolic networks.

Authors:  Matthias P Gerstl; David E Ruckerbauer; Diethard Mattanovich; Christian Jungreuthmayer; Jürgen Zanghellini
Journal:  Sci Rep       Date:  2015-03-10       Impact factor: 4.379

4.  Avoiding the Enumeration of Infeasible Elementary Flux Modes by Including Transcriptional Regulatory Rules in the Enumeration Process Saves Computational Costs.

Authors:  Christian Jungreuthmayer; David E Ruckerbauer; Matthias P Gerstl; Michael Hanscho; Jürgen Zanghellini
Journal:  PLoS One       Date:  2015-06-19       Impact factor: 3.240

Review 5.  Yeast as a cell factory: current state and perspectives.

Authors:  Martin Kavšček; Martin Stražar; Tomaž Curk; Klaus Natter; Uroš Petrovič
Journal:  Microb Cell Fact       Date:  2015-06-30       Impact factor: 5.328

6.  Elementary Vectors and Conformal Sums in Polyhedral Geometry and their Relevance for Metabolic Pathway Analysis.

Authors:  Stefan Müller; Georg Regensburger
Journal:  Front Genet       Date:  2016-05-24       Impact factor: 4.599

7.  Design of optimally constructed metabolic networks of minimal functionality.

Authors:  David E Ruckerbauer; Christian Jungreuthmayer; Jürgen Zanghellini
Journal:  PLoS One       Date:  2014-03-25       Impact factor: 3.240

8.  Comparison and improvement of algorithms for computing minimal cut sets.

Authors:  Christian Jungreuthmayer; Govind Nair; Steffen Klamt; Jürgen Zanghellini
Journal:  BMC Bioinformatics       Date:  2013-11-06       Impact factor: 3.169

9.  DRUM: a new framework for metabolic modeling under non-balanced growth. Application to the carbon metabolism of unicellular microalgae.

Authors:  Caroline Baroukh; Rafael Muñoz-Tamayo; Jean-Philippe Steyer; Olivier Bernard
Journal:  PLoS One       Date:  2014-08-08       Impact factor: 3.240

10.  Designing overall stoichiometric conversions and intervening metabolic reactions.

Authors:  Anupam Chowdhury; Costas D Maranas
Journal:  Sci Rep       Date:  2015-11-04       Impact factor: 4.379
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