Stability cannot be derived from local structure in biochemical networks

  • Authors:

  • Domenico Bellomo;Peter van Nes;Marcel J. T. Reinders;Dick de Ridder

  • Affiliations:

  • Delft University of Technology, The Netherlands;Delft University of Technology, The Netherlands;Delft University of Technology, The Netherlands;Delft University of Technology, The Netherlands

  • Venue:
  • Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems
  • Year:
  • 2008

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Abstract

In recent literature, the relationship between structure and dynamics in biochemical networks has been intensively investigated. In fact, the scarcity of information about such networks has led to attempts to predict some of their dynamic features based exclusively on more easily available structural information. A recent finding relating structure to dynamics is that network motifs (a structural feature) that are structurally stable (a dynamic feature) are enriched in some biochemical networks [21]. In this work, we systematically investigate the method in [21] and the assumptions it relies on. Our findings suggest that the conclusions drawn on the considered biological networks (over-representation of structurally stable motifs) cannot be generalized, as they critically depend on a user-defined choice of null model in the motif enrichment analysis. We have further applied the method in [21] to metabolic networks, which provide an excellent test-bed, as a relatively large amount of information is available about the type, strength and activity of metabolic interactions. For metabolic networks we arrive at the same conclusion: stability cannot be derived from local structure.