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

MPS-Authors
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Klamt,  S.
Systems Biology, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Stelling,  J.
Systems Biology, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Ginkel,  Martin
Systems Biology, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Gilles,  E. D.
Systems Biology, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Citation

Klamt, S., Stelling, J., Ginkel, M., & Gilles, E. D. (2003). FluxAnalyzer: exploring structure, pathways, and flux distributions in metabolic networks on interactive flux maps. Bioinformatics, 19(2), 261-269. doi:10.1093/bioinformatics/19.2.261.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-9F7D-5
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(R) 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. Copyright © 2013 Oxford University Press [accessed 2013 June 13th]