A Reduction of Logical Regulatory Graphs Preserving Essential Dynamical Properties

  • Aurélien Naldi
  • Elisabeth Remy
  • Denis Thieffry
  • Claudine Chaouiya
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5688)


To cope with the increasing complexity of regulatory networks, we define a reduction method for multi-valued logical models.

Starting with a detailed model, this method enables the computation of a reduced model by iteratively “hiding” regulatory components. To keep a consistent behaviour, the logical rules associated with the targets of each hidden node are actualised to account for the (indirect) effects of its regulators.

The construction of reduced models ensures the preservation of a number of dynamical properties of the original model. In particular, stable states and more complex attractors are conserved. More generally, we focus on the relationship between the attractor configuration of the original model and that of the reduced model, along with the issue of attractor reachability.

The power of the reduction method is illustrated by its application to a multi-valued model of the segment-polarity network Controlling segmentation in the fly Drosophila melanogaster.


Regulatory networks logical modelling model reduction decision diagrams regulatory circuits stable states complex attractors Drosophila development segmentation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Aurélien Naldi
    • 1
  • Elisabeth Remy
    • 2
  • Denis Thieffry
    • 1
    • 3
  • Claudine Chaouiya
    • 1
    • 4
  1. 1.TAGC Inserm U928Université de la MéditerranéeMarseilleFrance
  2. 2.IML UMR 6206MarseilleFrance
  3. 3.CONTRAINTESINRIA Paris RocquencourtFrance
  4. 4.IGCInstituto Gulbenkian de CiênciaOeirasPortugal

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