Stability from structure: metabolic networks are unlike other biological networks

  • Authors:

  • P. van Nes;D. Bellomo;M. J. T. Reinders;D. de Ridder

  • Affiliations:

  • Information and Communication Theory Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands;Faculty of Electrical Engineering, Mathematics and Computer Science and Bioprocess Technology Section, Delft University of Technology and Kluyver Centre for Genomics of Industrial Fermentation, De ...;Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands and Kluyver Centre for Genomics of Industrial Fermentation, Delft, The N ...;Information and Communication Theory Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands and Kluyver Centre for Genom ...

  • Venue:
  • EURASIP Journal on Bioinformatics and Systems Biology - Special issue on network structure and biological function: Reconstruction, modelling, and statistical approaches
  • Year:
  • 2009

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Abstract

In recent work, attempts have been made to link the structure of biochemical networks to their complex dynamics. It was shown that structurally stable network motifs are enriched in such networks. In this work, we investigate to what extent these findings apply to metabolic networks. To this end, we extend a previously proposed method by changing the null model for determining motif enrichment, by using interaction types directly obtained from structural interaction matrices, by generating a distribution of partial derivatives of reaction rates and by simulating enzymatic regulation on metabolic networks. Our findings suggest that the conclusions drawn in previous work cannot be extended to metabolic networks, that is, structurally stable network motifs are not enriched in metabolic networks.