Literature DB >> 19015845

Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism.

Cong T Trinh1, Aaron Wlaschin, Friedrich Srienc.   

Abstract

Elementary mode analysis is a useful metabolic pathway analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering.

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Year:  2008        PMID: 19015845      PMCID: PMC2909134          DOI: 10.1007/s00253-008-1770-1

Source DB:  PubMed          Journal:  Appl Microbiol Biotechnol        ISSN: 0175-7598            Impact factor:   4.813


  87 in total

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Authors:  Jörg Stelling; Steffen Klamt; Katja Bettenbrock; Stefan Schuster; Ernst Dieter Gilles
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2.  The genome-scale metabolic extreme pathway structure in Haemophilus influenzae shows significant network redundancy.

Authors:  Jason A Papin; Nathan D Price; Jeremy S Edwards; Bernhard Ø Palsson B
Journal:  J Theor Biol       Date:  2002-03-07       Impact factor: 2.691

3.  Application of Petri net theory for modelling and validation of the sucrose breakdown pathway in the potato tuber.

Authors:  Ina Koch; Björn H Junker; Monika Heiner
Journal:  Bioinformatics       Date:  2004-11-16       Impact factor: 6.937

4.  Metabolic pathway structures for recombinant protein synthesis in Escherichia coli.

Authors:  Natarajan Vijayasankaran; Ross Carlson; Friedrich Srienc
Journal:  Appl Microbiol Biotechnol       Date:  2005-10-13       Impact factor: 4.813

5.  Combinatorial complexity of pathway analysis in metabolic networks.

Authors:  Steffen Klamt; Jörg Stelling
Journal:  Mol Biol Rep       Date:  2002       Impact factor: 2.316

6.  Modular decomposition of metabolic systems via null-space analysis.

Authors:  Mark G Poolman; Cristiana Sebu; Michael K Pidcock; David A Fell
Journal:  J Theor Biol       Date:  2007-08-19       Impact factor: 2.691

7.  Computer-aided synthesis of biochemical pathways.

Authors:  M L Mavrovouniotis; G Stephanopoulos; G Stephanopoulos
Journal:  Biotechnol Bioeng       Date:  1990-12-20       Impact factor: 4.530

8.  Robustness analysis of the Escherichia coli metabolic network.

Authors:  J S Edwards; B O Palsson
Journal:  Biotechnol Prog       Date:  2000 Nov-Dec

9.  Design, construction and performance of the most efficient biomass producing E. coli bacterium.

Authors:  Cong T Trinh; Ross Carlson; Aaron Wlaschin; Friedrich Srienc
Journal:  Metab Eng       Date:  2006-08-15       Impact factor: 9.783

10.  SNA--a toolbox for the stoichiometric analysis of metabolic networks.

Authors:  Robert Urbanczik
Journal:  BMC Bioinformatics       Date:  2006-03-13       Impact factor: 3.169

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  73 in total

Review 1.  Succinate production in Escherichia coli.

Authors:  Chandresh Thakker; Irene Martínez; Ka-Yiu San; George N Bennett
Journal:  Biotechnol J       Date:  2011-09-20       Impact factor: 4.677

Review 2.  Identification of aberrant pathways and network activities from high-throughput data.

Authors:  Jinlian Wang; Yuji Zhang; Catalin Marian; Habtom W Ressom
Journal:  Brief Bioinform       Date:  2012-01-27       Impact factor: 11.622

3.  BioNetSim: a Petri net-based modeling tool for simulations of biochemical processes.

Authors:  Junhui Gao; Li Li; Xiaolin Wu; Dong-Qing Wei
Journal:  Protein Cell       Date:  2012-03-10       Impact factor: 14.870

4.  Analysis of metabolic subnetworks by flux cone projection.

Authors:  Sayed-Amir Marashi; Laszlo David; Alexander Bockmayr
Journal:  Algorithms Mol Biol       Date:  2012-05-29       Impact factor: 1.405

Review 5.  Systems strategies for developing industrial microbial strains.

Authors:  Sang Yup Lee; Hyun Uk Kim
Journal:  Nat Biotechnol       Date:  2015-10       Impact factor: 54.908

Review 6.  Recent advances in elementary flux modes and yield space analysis as useful tools in metabolic network studies.

Authors:  Predrag Horvat; Martin Koller; Gerhart Braunegg
Journal:  World J Microbiol Biotechnol       Date:  2015-06-12       Impact factor: 3.312

Review 7.  Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods.

Authors:  Nathan E Lewis; Harish Nagarajan; Bernhard O Palsson
Journal:  Nat Rev Microbiol       Date:  2012-02-27       Impact factor: 60.633

8.  Complete enumeration of elementary flux modes through scalable demand-based subnetwork definition.

Authors:  Kristopher A Hunt; James P Folsom; Reed L Taffs; Ross P Carlson
Journal:  Bioinformatics       Date:  2014-02-03       Impact factor: 6.937

9.  Pathway discovery in metabolic networks by subgraph extraction.

Authors:  Karoline Faust; Pierre Dupont; Jérôme Callut; Jacques van Helden
Journal:  Bioinformatics       Date:  2010-03-12       Impact factor: 6.937

10.  Flux Design: In silico design of cell factories based on correlation of pathway fluxes to desired properties.

Authors:  Guido Melzer; Manely Eslahpazir Esfandabadi; Ezequiel Franco-Lara; Christoph Wittmann
Journal:  BMC Syst Biol       Date:  2009-12-25
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