Literature DB >> 24728852

Direct calculation of elementary flux modes satisfying several biological constraints in genome-scale metabolic networks.

Jon Pey1, Francisco J Planes1.   

Abstract

MOTIVATION: The concept of Elementary Flux Mode (EFM) has been widely used for the past 20 years. However, its application to genome-scale metabolic networks (GSMNs) is still under development because of methodological limitations. Therefore, novel approaches are demanded to extend the application of EFMs. A novel family of methods based on optimization is emerging that provides us with a subset of EFMs. Because the calculation of the whole set of EFMs goes beyond our capacity, performing a selective search is a proper strategy.
RESULTS: Here, we present a novel mathematical approach calculating EFMs fulfilling additional linear constraints. We validated our approach based on two metabolic networks in which all the EFMs can be obtained. Finally, we analyzed the performance of our methodology in the GSMN of the yeast Saccharomyces cerevisiae by calculating EFMs producing ethanol with a given minimum carbon yield. Overall, this new approach opens new avenues for the calculation of EFMs in GSMNs.
AVAILABILITY AND IMPLEMENTATION: Matlab code is provided in the supplementary online materials CONTACT: fplanes@ceit.es. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2014        PMID: 24728852     DOI: 10.1093/bioinformatics/btu193

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  10 in total

1.  Finding MEMo: minimum sets of elementary flux modes.

Authors:  Annika Röhl; Alexander Bockmayr
Journal:  J Math Biol       Date:  2019-08-06       Impact factor: 2.259

2.  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

3.  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 4.  From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints.

Authors:  Steffen Klamt; Georg Regensburger; Matthias P Gerstl; Christian Jungreuthmayer; Stefan Schuster; Radhakrishnan Mahadevan; Jürgen Zanghellini; Stefan Müller
Journal:  PLoS Comput Biol       Date:  2017-04-13       Impact factor: 4.475

5.  Boosting the extraction of elementary flux modes in genome-scale metabolic networks using the linear programming approach.

Authors:  Francisco Guil; José F Hidalgo; José M García
Journal:  Bioinformatics       Date:  2020-08-15       Impact factor: 6.937

6.  Principal metabolic flux mode analysis.

Authors:  Sahely Bhadra; Peter Blomberg; Sandra Castillo; Juho Rousu
Journal:  Bioinformatics       Date:  2018-07-15       Impact factor: 6.937

7.  Unlocking Elementary Conversion Modes: ecmtool Unveils All Capabilities of Metabolic Networks.

Authors:  Tom J Clement; Erik B Baalhuis; Bas Teusink; Frank J Bruggeman; Robert Planqué; Daan H de Groot
Journal:  Patterns (N Y)       Date:  2020-12-29

8.  Which sets of elementary flux modes form thermodynamically feasible flux distributions?

Authors:  Matthias P Gerstl; Christian Jungreuthmayer; Stefan Müller; Jürgen Zanghellini
Journal:  FEBS J       Date:  2016-03-31       Impact factor: 5.542

9.  Improving the EFMs quality by augmenting their representativeness in LP methods.

Authors:  José F Hidalgo; Jose A Egea; Francisco Guil; José M García
Journal:  BMC Syst Biol       Date:  2018-11-20

10.  Elementary vectors and autocatalytic sets for resource allocation in next-generation models of cellular growth.

Authors:  Stefan Müller; Diana Széliová; Jürgen Zanghellini
Journal:  PLoS Comput Biol       Date:  2022-02-01       Impact factor: 4.475

  10 in total

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