data structures and software dependability

computer science department

brandenburg university of technology cottbus - senftenberg

NoPain The Nociceptor Pain Model

Funding Number: FKZ0316177E


latest update: March 23, 2019, at 02:04 PM

Project description

  • This project applies established mathematical models of signalling switches involved in pain sensitisation, optimises and expands them by reflection on molecular, cellular as well as animal experiments, to finally apply their predictive power to humans enabling a "mechanism-based" pain therapy.
  • This project involves 7 teams, one of them at the BTU Cottbus, chaired by Prof. Heiner. In this team, the objective is to apply qualitative, stochastic, and continuous Petri nets to modeling and analysis of pain switches.
  • duration: January 2013 - December 2015


In the BTU team, Petri nets are applied to modeling and analysis of the nociceptor pain model, which allow the application of powerful analysis techniques ranging from graph theory, linear algebra via model checking to simulation methods. The Petri net formalism is extremely powerful for modelling the nociception network because it can represent different mechanisms and data types, like the activity of extracellular mediators, signal transducers, intracellular second messengers including their spatial distribution in the cell or tissue, effectors such as ion channels, and membrane potential changes to even subjectively graded parameters like pain in a time-resolved manner.

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