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  Subnetwork analysis reveals dynamic features of complex (bio)chemical networks

Conradi, C., Flockerzi, D., Raisch, J., & Stelling, J. (2007). Subnetwork analysis reveals dynamic features of complex (bio)chemical networks. PNAS, 104(49), 19175-19180. doi:10.1073/pnas.0705731104.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-96EB-8 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0025-B3B2-5
Genre: Journal Article

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 Creators:
Conradi, C.1, Author              
Flockerzi, D.1, Author              
Raisch, J.1, 2, Author              
Stelling, J.3, Author
Affiliations:
1Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738154              
2TU Berlin, ou_persistent22              
3Institute of Computational Science and Swiss Institute of Bioinformatics, Swiss Federal Institute of Technology Zurich, 8092 Zurich, Switzerland , ou_persistent22              

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 Abstract: In analyzing and mathematical modeling of complex (bio)chemical reaction networks, formal methods that connect network structure and dynamic behavior are needed because often, quantitative knowledge of the networks is very limited. This applies to many important processes in cell biology. Chemical reaction network theory allows for the classification of the potential network behavior—for instance, with respect to the existence of multiple steady states—but is computationally limited to small systems. Here, we show that by analyzing subnetworks termed elementary flux modes, the applicability of the theory can be extended to more complex networks. For an example network inspired by cell cycle control in budding yeast, the approach allows for model discrimination, identification of key mechanisms for multistationarity, and robustness analysis. The presented methods will be helpful in modeling and analyzing other complex reaction networks. Copyright © 2013 National Academy of Sciences [access 2013 June 14th]

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Language(s): eng - English
 Dates: 2007
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1073/pnas.0705731104
eDoc: 319732
Other: 24/07
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Title: PNAS
Source Genre: Journal
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Pages: - Volume / Issue: 104 (49) Sequence Number: - Start / End Page: 19175 - 19180 Identifier: -