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Multi-valued network models are an important qualitative modelling approachused widely by the biological community. In this paper we consider developingan abstraction theory for multi-valued network models that allows the statespace 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-valuednetworks and in particular, helps address the well-known problem of state spaceexplosion associated with such analysis. We also consider developing techniquesfor efficiently identifying abstractions and so provide a basis for theautomation of this task. We illustrate the theory and techniques developed byinvestigating the identification of abstractions for two published MVN modelsof the lysis-lysogeny switch in the bacteriophage lambda.

An Abstraction Theory for Qualitative Models of Biological Systems