Towards Paraconsistent Engineering

Volume 110 of the series Intelligent Systems Reference Library pp 205-226


Temporal Logic Modeling of Biological Systems

  • Jean-Marc AlliotAffiliated withINSERM/IRIT, University of Toulouse
  • , Robert DemolombeAffiliated withINSERM/IRIT, University of Toulouse
  • , Martín DiéguezAffiliated withINSERM/IRIT, University of Toulouse
  • , Luis Fariñas del CerroAffiliated withINSERM/IRIT, University of Toulouse Email author 
  • , Gilles FavreAffiliated withINSERM/IRIT, University of Toulouse
  • , Jean-Charles FayeAffiliated withINSERM/IRIT, University of Toulouse
  • , Naji ObeidAffiliated withINSERM/IRIT, University of Toulouse
  • , Olivier SordetAffiliated withINSERM/IRIT, University of Toulouse

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Metabolic networks, formed by a series of metabolic pathways, are made of intracellular and extracellular reactions that determine the biochemical properties of a cell, and by a set of interactions that guide and regulate the activity of these reactions. Cancer, for example, can sometimes appear in a cell as a result of some pathology in a metabolic pathway. Most of these pathways are formed by an intricate and complex network of chain reactions, and can be represented in a human readable form using graphs which describe the cell signaling pathways. In this paper, we define a logic, called Molecular Interaction Logic (MIL), able to represent these graphs and we present a method to automatically translate graphs into MIL formulas. Then we show how MIL formulas can be translated into linear time temporal logic, and then grounded into propositional classical logic. This enables us to solve complex queries on graphs using only propositional classical reasoning tools such as SAT solvers.


Metabolic networks Molecular interaction logic (MIL) Temporal reasoning