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  Visualizing Regulatory Interactions in Metabolic Networks

Noack, S., Wahl, A., Qeli, E., & Wiechert, W. (2007). Visualizing Regulatory Interactions in Metabolic Networks. BMC Biology, 5, 46. doi:10.1186/1741-7007-5-46.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-98ED-3 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002C-8A3F-C
Genre: Journal Article

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eDoc_322144_2007.pdf (Publisher version), 980KB
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© 2007 Noack et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the orig inal work is properly cited.

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 Creators:
Noack, S.1, Author
Wahl, A.2, Author              
Qeli, E.3, Author
Wiechert, W.4, Author
Affiliations:
1Research Centre Jülich, Institute of Biotechnology 2, Germany, ou_persistent22              
2Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738140              
3University of Marburg, Department of Mathematics and Computer Science, Germany, ou_persistent22              
4University of Siegen, Institute of Systems Engineerin g, Department of Simulation, Germany, ou_persistent22              

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 Abstract: Background Direct visualization of data sets in the context of biochemical network drawings is one of the most appealing approaches in the field of data evaluation within systems biology. One important type of information that is very helpful in interpreting and understanding metabolic networks has been overlooked so far. Here we focus on the representation of this type of information given by the strength of regulatory interactions between metabolite pools and reaction steps. Results The visualization of such interactions in a given metabolic network is based on a novel concept defining the regulatory strength (RS) of effectors regulating certain reaction steps. It is applicable to any mechanistic reaction kinetic formula. The RS values are measures for the strength of an up- or down-regulation of a reaction step compared with the completely non-inhibited or non-activated state, respectively. One numerical RS value is associated to any effector edge contained in the network. The RS is approximately interpretable on a percentage scale where 100% means the maximal possible inhibition or activation, respectively, and 0% means the absence of a regulatory interaction. If many effectors influence a certain reaction step, the respective percentages indicate the proportion in which the different effectors contribute to the total regulation of the reaction step. The benefits of the proposed method are demonstrated with a complex example system of a dynamic E. coli network. Conclusions The presented visualization approach is suitable for an intuitive interpretation of simulation data of metabolic networks under dynamic as well as steady-state conditions. Huge amounts of simulation data can be analyzed in a quick and comprehensive way. An extended time-resolved graphical network presentation provides a series of information about regulatory interaction within the biological system under investigation. © 2007 Noack et al; licensee BioMed Central Ltd.

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Language(s): eng - English
 Dates: 2007
 Publication Status: Published in print
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 Rev. Method: Peer
 Identifiers: eDoc: 322144
DOI: 10.1186/1741-7007-5-46
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Title: BMC Biology
Source Genre: Journal
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Pages: - Volume / Issue: 5 Sequence Number: - Start / End Page: 46 Identifier: ISSN: 1741-7007