Literature DB >> 12538248

FluxAnalyzer: exploring structure, pathways, and flux distributions in metabolic networks on interactive flux maps.

Steffen Klamt1, Jörg Stelling, Martin Ginkel, Ernst Dieter Gilles.   

Abstract

MOTIVATION: The analysis of structure, pathways and flux distributions in metabolic networks has become an important approach for understanding the functionality of metabolic systems. The need of a user-friendly platform for stoichiometric modeling of metabolic networks in silico is evident.
RESULTS: The FluxAnalyzer is a package for MATLAB and facilitates integrated pathway and flux analysis for metabolic networks within a graphical user interface. Arbitrary metabolic network models can be composed by instances of four types of network elements. The abstract network model is linked with network graphics leading to interactive flux maps which allow for user input and display of calculation results within a network visualization. Therein, a large and powerful collection of tools and algorithms can be applied interactively including metabolic flux analysis, flux optimization, detection of topological features and pathway analysis by elementary flux modes or extreme pathways. The FluxAnalyzer has been applied and tested for complex networks with more than 500,000 elementary modes. Some aspects of the combinatorial complexity of pathway analysis in metabolic networks are discussed. AVAILABILITY: Upon request from the corresponding author. Free for academic users (license agreement). Special contracts are available for industrial corporations. SUPPLEMENTARY INFORMATION: http://www.mpi-magdeburg.mpg.de/projects/fluxanalyzer.

Mesh:

Year:  2003        PMID: 12538248     DOI: 10.1093/bioinformatics/19.2.261

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


  56 in total

1.  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

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

3.  Metabolic response of perfused livers to various oxygenation conditions.

Authors:  Mehmet A Orman; Marianthi G Ierapetritou; Ioannis P Androulakis; Francois Berthiaume
Journal:  Biotechnol Bioeng       Date:  2011-08-04       Impact factor: 4.530

Review 4.  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

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

6.  Environments that induce synthetic microbial ecosystems.

Authors:  Niels Klitgord; Daniel Segrè
Journal:  PLoS Comput Biol       Date:  2010-11-18       Impact factor: 4.475

7.  A protocol for generating a high-quality genome-scale metabolic reconstruction.

Authors:  Ines Thiele; Bernhard Ø Palsson
Journal:  Nat Protoc       Date:  2010-01-07       Impact factor: 13.491

8.  BioMet Toolbox: genome-wide analysis of metabolism.

Authors:  Marija Cvijovic; Roberto Olivares-Hernández; Rasmus Agren; Niklas Dahr; Wanwipa Vongsangnak; Intawat Nookaew; Kiran Raosaheb Patil; Jens Nielsen
Journal:  Nucleic Acids Res       Date:  2010-05-18       Impact factor: 16.971

Review 9.  Which metabolic pathways generate and characterize the flux space? A comparison among elementary modes, extreme pathways and minimal generators.

Authors:  Francisco Llaneras; Jesús Picó
Journal:  J Biomed Biotechnol       Date:  2010-05-11

10.  OptFlux: an open-source software platform for in silico metabolic engineering.

Authors:  Isabel Rocha; Paulo Maia; Pedro Evangelista; Paulo Vilaça; Simão Soares; José P Pinto; Jens Nielsen; Kiran R Patil; Eugénio C Ferreira; Miguel Rocha
Journal:  BMC Syst Biol       Date:  2010-04-19
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