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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, 75, 015101–1-015101–4. doi:10.1103/PhysRevE.75.015101.

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Kaluza, Pablo1, Author           
Ipsen, Mads1, Author           
Vingron, Martin2, Author
Mikhailov, Alexander S.1, Author           
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1Physical Chemistry, Fritz Haber Institute, Max Planck Society, ou_634546              
2Max Planck Society, ou_persistent13              

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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
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 Rev. Type: Peer
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Title: Physical Review E
  Alternative Title : Phys. Rev. E
Source Genre: Journal
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Pages: - Volume / Issue: 75 Sequence Number: - Start / End Page: 015101–1 - 015101–4 Identifier: -