Literature DB >> 10222413

METATOOL: for studying metabolic networks.

T Pfeiffer1, I Sánchez-Valdenebro, J C Nuño, F Montero, S Schuster.   

Abstract

MOTIVATION: To reconstruct metabolic pathways from biochemical and/or genome sequence data, the stoichiometric and thermodynamic feasibility of the pathways has to be tested. This is achieved by characterizing the admissible region of flux distributions in steady state. This region is spanned by what can be called a convex basis. The concept of 'elementary flux modes' provides a mathematical tool to define all metabolic routes that are feasible in a given metabolic network. In addition, we define 'enzyme subsets' to be groups of enzymes that operate together in fixed flux proportions in all steady states of the system.
RESULTS: Algorithms for computing the convex basis and elementary modes developed earlier are briefly reviewed. A newly developed algorithm for detecting all enzyme subsets in a given network is presented. All of these algorithms have been implemented in a novel computer program named METATOOL, whose features are outlined here. The algorithms are illustrated by an example taken from sugar metabolism. AVAILABILITY: METATOOL is available from ftp://bmsdarwin.brookes.ac. uk/pub/software/ibmpc/metatool. SUPPLEMENTARY INFORMATION: http://www. biologie.hu-berlin.de/biophysics/Theory/tpfeiffer/metatoo l.html

Entities:  

Mesh:

Substances:

Year:  1999        PMID: 10222413     DOI: 10.1093/bioinformatics/15.3.251

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


  84 in total

1.  Pathway alignment: application to the comparative analysis of glycolytic enzymes.

Authors:  T Dandekar; S Schuster; B Snel; M Huynen; P Bork
Journal:  Biochem J       Date:  1999-10-01       Impact factor: 3.857

Review 2.  Metabolomics--the link between genotypes and phenotypes.

Authors:  Oliver Fiehn
Journal:  Plant Mol Biol       Date:  2002-01       Impact factor: 4.076

3.  GeneCensus: genome comparisons in terms of metabolic pathway activity and protein family sharing.

Authors:  J Lin; J Qian; D Greenbaum; P Bertone; R Das; N Echols; A Senes; B Stenger; M Gerstein
Journal:  Nucleic Acids Res       Date:  2002-10-15       Impact factor: 16.971

Review 4.  Network genomics--a novel approach for the analysis of biological systems in the post-genomic era.

Authors:  Christian V Forst
Journal:  Mol Biol Rep       Date:  2002-09       Impact factor: 2.316

5.  Extreme pathway lengths and reaction participation in genome-scale metabolic networks.

Authors:  Jason A Papin; Nathan D Price; Bernhard Ø Palsson
Journal:  Genome Res       Date:  2002-12       Impact factor: 9.043

6.  Dynamic generation and qualitative analysis of metabolic pathways by a joint database/graph theoretical approach.

Authors:  F Ehrentreich; D Schomburg
Journal:  Funct Integr Genomics       Date:  2003-10-16       Impact factor: 3.410

7.  Flux coupling analysis of genome-scale metabolic network reconstructions.

Authors:  Anthony P Burgard; Evgeni V Nikolaev; Christophe H Schilling; Costas D Maranas
Journal:  Genome Res       Date:  2004-01-12       Impact factor: 9.043

8.  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

9.  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

10.  Elucidation and structural analysis of conserved pools for genome-scale metabolic reconstructions.

Authors:  Evgeni V Nikolaev; Anthony P Burgard; Costas D Maranas
Journal:  Biophys J       Date:  2004-10-15       Impact factor: 4.033

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.