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Natural Computing

Erschienen in:

01.06.2011

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

verfasst von: Wolfgang Marwan, Annegret Wagler, Robert Weismantel

Erschienen in: Natural Computing | Ausgabe 2/2011

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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.

Vorheriger Artikel Preface: Petri nets for Systems and Synthetic Biology

Nächster Artikel The combinatorics of modeling and analyzing biological systems

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Titel: Petri nets as a framework for the reconstruction and analysis of signal transduction pathways and regulatory networks
verfasst von: Wolfgang Marwan
Annegret Wagler
Robert Weismantel
Publikationsdatum: 01.06.2011
Verlag: Springer Netherlands
Erschienen in: Natural Computing / Ausgabe 2/2011
Print ISSN: 1567-7818
Elektronische ISSN: 1572-9796
DOI: https://doi.org/10.1007/s11047-009-9152-x

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