Literature DB >> 16188931

Functional stoichiometric analysis of metabolic networks.

R Urbanczik1, C Wagner.   

Abstract

MOTIVATION: An important tool in Systems Biology is the stoichiometric modeling of metabolic networks, where the stationary states of the network are described by a high-dimensional polyhedral cone, the so-called flux cone. Exhaustive descriptions of the metabolism can be obtained by computing the elementary vectors of this cone but, owing to a combinatorial explosion of the number of elementary vectors, this approach becomes computationally intractable for genome scale networks. RESULT: Hence, we propose to instead focus on the conversion cone, a projection of the flux cone, which describes the interaction of the metabolism with its external chemical environment. We present a direct method for calculating the elementary vectors of this cone and, by studying the metabolism of Saccharomyces cerevisiae, we demonstrate that such an analysis is computationally feasible even for genome scale networks.

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Year:  2005        PMID: 16188931     DOI: 10.1093/bioinformatics/bti674

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


  20 in total

1.  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

2.  On algebraic properties of extreme pathways in metabolic networks.

Authors:  Dimitrije Jevremovic; Cong T Trinh; Friedrich Srienc; Daniel Boley
Journal:  J Comput Biol       Date:  2010-02       Impact factor: 1.479

Review 3.  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

4.  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

5.  Parallelization of Nullspace Algorithm for the computation of metabolic pathways.

Authors:  Dimitrije Jevremović; Cong T Trinh; Friedrich Srienc; Carlos P Sosa; Daniel Boley
Journal:  Parallel Comput       Date:  2011-06       Impact factor: 0.986

Review 6.  Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism.

Authors:  Cong T Trinh; Aaron Wlaschin; Friedrich Srienc
Journal:  Appl Microbiol Biotechnol       Date:  2008-11-15       Impact factor: 4.813

7.  Understanding FBA Solutions under Multiple Nutrient Limitations.

Authors:  Eunice van Pelt-KleinJan; Daan H de Groot; Bas Teusink
Journal:  Metabolites       Date:  2021-04-21

8.  Optimal flux spaces of genome-scale stoichiometric models are determined by a few subnetworks.

Authors:  Steven M Kelk; Brett G Olivier; Leen Stougie; Frank J Bruggeman
Journal:  Sci Rep       Date:  2012-08-15       Impact factor: 4.379

9.  F2C2: a fast tool for the computation of flux coupling in genome-scale metabolic networks.

Authors:  Abdelhalim Larhlimi; Laszlo David; Joachim Selbig; Alexander Bockmayr
Journal:  BMC Bioinformatics       Date:  2012-04-23       Impact factor: 3.169

10.  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

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