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  Design and statistical properties of robust functional networks: A model study of biological signal transduction.

Kaluza, P., Ipsen, M., Vingron, M., & Mikhailov, A. S. (2007). Design and statistical properties of robust functional networks: A model study of biological signal transduction. Physical Review: E, Statistical, Nonlinear and Soft Matter Physics, E75: 015101. doi:10.1103/PhysRevE.75.015101.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0010-8264-A Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0010-8265-8
Genre: Journal Article
Alternative Title : Phys Rev E : Stat Nonlin Soft Matter Phys.

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 Creators:
Kaluza, Pablo1, Author
Ipsen, Mads, Author
Vingron, Martin2, Author           
Mikhailov, Alexander S.1, Author
Affiliations:
1Max Planck Society, ou_persistent13              
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: cellular biophysics; signal processing; statistical analysis; genetics; optimisation
 Abstract: A simple flow network model of biological signal transduction is investigated. Networks with prescribed signal processing functions, robust against random node or link removals, are designed through an evolutionary optimization process. Statistical properties of large ensembles of such networks, including their characteristic motif distributions, are determined. Our analysis suggests that robustness against link removals plays the principal role in the architecture of real signal transduction networks and developmental genetic transcription networks.

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Language(s): eng - English
 Dates: 2007-01-19
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 336022
DOI: 10.1103/PhysRevE.75.015101
URI: http://scitation.aip.org/getpdf/servlet/GetPDFServlet?filetype=pdf&id=PLEEE8000075000001015101000001&idtype=cvips&prog=normal
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Title: Physical Review : E, Statistical, Nonlinear and Soft Matter Physics
  Alternative Title : Phys Rev E : Stat Nonlin Soft Matter Phys.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: E75 Sequence Number: 015101 Start / End Page: - Identifier: ISSN: 1063-651X