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

Kaluza, Pablo; Ipsen, Mads; Vingron, Martin; Mikhailov, Alexander S.

doi:10.1103/PhysRevE.75.015101

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

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Kaluza, Pablo
Max Planck Society;

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Vingron, Martin
Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

Mikhailov, Alexander S.
Max Planck Society;

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Citation

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.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0010-8264-A

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.