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Natural Computing

, Volume 10, Issue 2, pp 639–654 | Cite as

Petri nets as a framework for the reconstruction and analysis of signal transduction pathways and regulatory networks

  • Wolfgang MarwanEmail author
  • Annegret Wagler
  • Robert Weismantel
Article

Abstract

Petri nets are directed, weighted bipartite graphs that have successfully been applied to the systems biology of metabolic and signal transduction pathways in modeling both stochastic (discrete) and deterministic (continuous) processes. Here we exemplify how molecular mechanisms, biochemical or genetic, can be consistently respresented in the form of place/transition Petri nets. We then describe the application of Petri nets to the reconstruction of molecular and genetic networks from experimental data and their power to represent biological processes with arbitrary degree of resolution of the subprocesses at the cellular and the molecular level. Petri nets are executable formal language models that permit the unambiguous visualization of regulatory mechanisms, and they can be used to encode the results of mathematical algorithms for the reconstruction of causal interaction networks from experimental time series data.

Keywords

Hierarchical Petri net Network reconstruction Automatic network reconstruction Formal language Systems biology 

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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Wolfgang Marwan
    • 1
    • 2
    Email author
  • Annegret Wagler
    • 1
  • Robert Weismantel
    • 1
  1. 1.Magdeburg Centre for Systems Biology (MaCS)Otto-von-Guericke-UniversitätMagdeburgGermany
  2. 2.Max-Planck-Institut für Dynamik komplexer technischer SystemeMagdeburgGermany

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