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Modelling the Structure and Dynamics of Biological Pathways

Author

Listed:
  • Laura O’Hara
  • Alessandra Livigni
  • Thanos Theo
  • Benjamin Boyer
  • Tim Angus
  • Derek Wright
  • Sz-Hau Chen
  • Sobia Raza
  • Mark W Barnett
  • Paul Digard
  • Lee B Smith
  • Tom C Freeman

Abstract

There is a need for formalised diagrams that both summarise current biological pathway knowledge and support modelling approaches that explain and predict their behaviour. Here, we present a new, freely available modelling framework that includes a biologist-friendly pathway modelling language (mEPN), a simple but sophisticated method to support model parameterisation using available biological information; a stochastic flow algorithm that simulates the dynamics of pathway activity; and a 3-D visualisation engine that aids understanding of the complexities of a system’s dynamics. We present example pathway models that illustrate of the power of approach to depict a diverse range of systems.This Community Page presents a biologist-friendly method for compiling detailed graphical models of biological pathways from the literature, including their subsequent parameterization for use in dynamic simulations of their activity.

Suggested Citation

  • Laura O’Hara & Alessandra Livigni & Thanos Theo & Benjamin Boyer & Tim Angus & Derek Wright & Sz-Hau Chen & Sobia Raza & Mark W Barnett & Paul Digard & Lee B Smith & Tom C Freeman, 2016. "Modelling the Structure and Dynamics of Biological Pathways," PLOS Biology, Public Library of Science, vol. 14(8), pages 1-16, August.
    • Handle: RePEc:plo:pbio00:1002530
    DOI: 10.1371/journal.pbio.1002530
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    References listed on IDEAS

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    1. Derek Ruths & Melissa Muller & Jen-Te Tseng & Luay Nakhleh & Prahlad T Ram, 2008. "The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks," PLOS Computational Biology, Public Library of Science, vol. 4(2), pages 1-15, February.
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