2010/11/02 by Richard Banks, L. Jason Steggles
Computer Science · #cs.CE #cs.DM
paper · pdf · doi:10.4204/eptcs.40.3
published as EPTCS 40, 2010, pp. 23-38 · In Proceedings MeCBIC 2010, arXiv:1011.0051
arxiv created 2010/11/02 · arxiv updated 2010/11/03
Multi-valued network models are an important qualitative modelling approach used widely by the biological community. In this paper we consider developing an abstraction theory for multi-valued network models that allows the state space of a model to be reduced while preserving key properties of the model. This is important as it aids the analysis and comparison of multi-valued networks and in particular, helps address the well-known problem of state space explosion associated with such analysis. We also consider developing techniques for efficiently identifying abstractions and so provide a basis for the automation of this task. We illustrate the theory and techniques developed by investigating the identification of abstractions for two published MVN models of the lysis-lysogeny switch in the bacteriophage lambda.