Open Access Open Badges Software

Integrated network reconstruction, visualization and analysis using YANAsquare

Roland Schwarz1, Chunguang Liang1, Christoph Kaleta2, Mark Kühnel7, Eik Hoffmann4, Sergei Kuznetsov4, Michael Hecker5, Gareth Griffiths7, Stefan Schuster6 and Thomas Dandekar13*

Author Affiliations

1 Department of Bioinformatics, Biocenter Am Hubland, D-97074 University of Würzburg, Germany

2 Bio Systems Analysis Group, Department of Mathematics and Computer Science, Friedrich Schiller University Jena, Germany

3 Structural and Computational Biology, EMBL Heidelberg, Germany

4 Department of Cell Biology and Biosystems Technology, Albert-Einstein-Str. 3, D-18059 University of Rostock, Germany

5 Institute for Microbiology, Friedrich-Ludwig-Jahn-Str. 15, D-17487 University of Greifswald, Germany

6 Department of Bioinformatics, Ernst-Abbe-Platz 2, D-07743 University of Jena, Germany

7 Cell Biology Program, EMBL Heidelberg, Germany

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BMC Bioinformatics 2007, 8:313  doi:10.1186/1471-2105-8-313

Published: 28 August 2007



Modeling of metabolic networks includes tasks such as network assembly, network overview, calculation of metabolic fluxes and testing the robustness of the network.


YANAsquare provides a software framework for rapid network assembly (flexible pathway browser with local or remote operation mode), network overview (visualization routine and YANAsquare editor) and network performance analysis (calculation of flux modes as well as target and robustness tests). YANAsquare comes as an easy-to-setup program package in Java. It is fully compatible and integrates the programs YANA (translation of gene expression values into flux distributions, metabolite network dissection) and Metatool (elementary mode calculation). As application examples we set-up and model the phospholipid network in the phagosome and genome-scale metabolic maps of S.aureus, S.epidermidis and S.saprophyticus as well as test their robustness against enzyme impairment.


YANAsquare is an application software for rapid setup, visualization and analysis of small, larger and genome-scale metabolic networks.