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PMID: 17408509 Published · epublish English Journal Article Research Support, Non-U.S. Gov't

Structural and functional analysis of cellular networks with CellNetAnalyzer.

BMC systems biology ·Vol. 1 ·2007-01-08 ·Pages 2

Klamt S, Saez-Rodriguez J, Gilles ED

Abstract

Mathematical modelling of cellular networks is an integral part of Systems Biology and requires appropriate software tools. An important class of methods in Systems Biology deals with structural or topological (parameter-free) analysis of cellular networks. So far, software tools providing such methods for both mass-flow (metabolic) as well as signal-flow (signalling and regulatory) networks are lacking. Herein we introduce CellNetAnalyzer, a toolbox for MATLAB facilitating, in an interactive and visual manner, a comprehensive structural analysis of metabolic, signalling and regulatory networks. The particular strengths of CellNetAnalyzer are methods for functional network analysis, i.e. for characterising functional states, for detecting functional dependencies, for identifying intervention strategies, or for giving qualitative predictions on the effects of perturbations. CellNetAnalyzer extends its predecessor FluxAnalyzer (originally developed for metabolic network and pathway analysis) by a new modelling framework for examining signal-flow networks. Two of the novel methods implemented in CellNetAnalyzer are discussed in more detail regarding algorithmic issues and applications: the computation and analysis (i) of shortest positive and shortest negative paths and circuits in interaction graphs and (ii) of minimal intervention sets in logical networks. CellNetAnalyzer provides a single suite to perform structural and qualitative analysis of both mass-flow- and signal-flow-based cellular networks in a user-friendly environment. It provides a large toolbox with various, partially unique, functions and algorithms for functional network analysis. CellNetAnalyzer is freely available for academic use.

MeSH Terms
Computer Simulation Escherichia coli/metabolism Metabolic Networks and Pathways Models, Biological Software Systems Biology/methods T-Lymphocytes/metabolism
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Klamt Steffen
Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, 39106 Magdeburg, Germany. [email protected]
Saez-Rodriguez Julio
Gilles Ernst D
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Article Info
Journal
BMC systems biology
Abbr.
BMC Syst Biol
ISSN
1752-0509
Published
2007-01-08
Epub
2007-00-08
Pages
2
Language
English
Region
England
NLM ID
101301827
PMCID
PMC1847467
Subset
IM
Analysis Services
Analysis Services

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