Rule-Based Modelling, Symmetries, Refinements

Rule-based modelling is particularly effective for handling the highly combinatorial aspects of cellular signalling. The dynamics is described in terms of interactions between partial complexes, and the ability to write rules with such partial complexes -i.e., not to have to specify all the traits of the entitities partaking in a reaction but just those that matter- is the key to obtaining compact descriptions of what otherwise could be nearly infinite dimensional dynamical systems. This also makes these descriptions easier to read, write and modify. In the course of modelling a particular signalling system it will often happen that more traits matter in a given interaction than previously thought, and one will need to strengthen the conditions under which that interaction may happen. This is a process that we call rule refinement and which we set out in this paper to study. Specifically we present a method to refine rule sets in a way that preserves the implied stochastic semantics. T...

• Type: Conference
• Year: 2008
• Where: FMSB
• Authors: Vincent Danos, Jérôme Feret, Walter Fontana, Russell Harmer, Jean Krivine
• Keywords: FMSB 2008, Formal Methods, Partial Complexes, Rule Refinement, Stochastic Semantics