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  An entropic characterization of protein interaction networks and cellular robustness

Manke, T., Demetrius, L., & Vingron, M. (2006). An entropic characterization of protein interaction networks and cellular robustness. Interface: Journal of the Royal Society, 11(3), 843-850. doi:10.1098/rsif.2006.0140.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-82FB-9 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-82FC-7
Genre: Journal Article
Alternative Title : J. R. Soc. Interface

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 Creators:
Manke, Thomas1, Author              
Demetrius, Lloyd1, Author              
Vingron, Martin2, Author              
Affiliations:
1Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              
2Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479639              

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Free keywords: network entropy, protein interactions, cellular robustness
 Abstract: The structure of molecular networks is believed to determine important aspects of their cellular function, such as the organismal resilience against random perturbations. Ultimately, however, cellular behaviour is determined by the dynamical processes, which are constrained by network topology. The present work is based on a fundamental relation from dynamical systems theory, which states that the macroscopic resilience of a steady state is correlated with the uncertainty in the underlying microscopic processes, a property that can be measured by entropy. Here, we use recent network data from large-scale protein interaction screens to characterize the diversity of possible pathways in terms of network entropy. This measure has its origin in statistical mechanics and amounts to a global characterization of both structural and dynamical resilience in terms of microscopic elements. We demonstrate how this approach can be used to rank network elements according to their contribution to network entropy and also investigate how this suggested ranking reflects on the functional data provided by gene knockouts and RNAi experiments in yeast and Caenorhabditis elegans. Our analysis shows that knockouts of proteins with large contribution to network entropy are preferentially lethal. This observation is robust with respect to several possible errors and biases in the experimental data. It underscores the significance of entropy as a fundamental invariant of the dynamical system, and as a measure of structural and dynamical properties of networks. Our analytical approach goes beyond the phenomenological studies of cellular robustness based on local network observables, such as connectivity. One of its principal achievements is to provide a rationale to study proxies of cellular resilience and rank proteins according to their importance within the global network context.

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Language(s): eng - English
 Dates: 2006-12-22
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: eDoc: 309923
DOI: 10.1098/rsif.2006.0140
 Degree: -

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Title: Interface : Journal of the Royal Society
  Alternative Title : J. R. Soc. Interface
Source Genre: Journal
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Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 11 (3) Sequence Number: - Start / End Page: 843 - 850 Identifier: ISSN: 1742-5689