Model Checking Gene Regulatory Networks

  • Mirco Giacobbe
  • Călin C. Guet
  • Ashutosh Gupta
  • Thomas A. Henzinger
  • Tiago Paixão
  • Tatjana Petrov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9035)


The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace this approach by a formal verification-like method that gives higher assurance and scalability. We focus on Wagner’s weighted GRN model with varying weights, which is used in evolutionary biology. In the model, weight parameters represent the gene interaction strength that may change due to genetic mutations. For a property of interest, we synthesise the constraints over the parameter space that represent the set of GRNs satisfying the property. We experimentally show that our parameter synthesis procedure computes the mutational robustness of GRNs -an important problem of interest in evolutionary biology- more efficiently than the classical simulation method. We specify the property in linear temporal logics. We employ symbolic bounded model checking and SMT solving to compute the space of GRNs that satisfy the property, which amounts to synthesizing a set of linear constraints on the weights.


Model Check Gene Regulatory Network Linear Temporal Logic Label Transition System Bound Model Check 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Mirco Giacobbe
    • 1
  • Călin C. Guet
    • 1
  • Ashutosh Gupta
    • 1
    • 2
  • Thomas A. Henzinger
    • 1
  • Tiago Paixão
    • 1
  • Tatjana Petrov
    • 1
  1. 1.IST AustriaKlosterneuburgAustria
  2. 2.TIFRMumbaiIndia

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