An Intuitive Automated Modelling Interface for Systems Biology

Abstract

We introduce a natural language interface for building stochastic p calculus models of biological systems. In this language, complex constructs describing biochemical events are built from basic primitives of association, dissociation and transformation. This language thus allows us to model biochemical systems modularly by describing their dynamics in a narrative-style language, while making amendments, refinements and extensions on the models easy. We give a formal semantics for this language and a translation algorithm into stochastic p calculus that delivers this semantics. We demonstrate the language on a model of Fcg receptor phosphorylation during phagocytosis. We provide a tool implementation of the translation into a stochastic p calculus language, Microsoft Research’s SPiM, which can be used for simulation and analysis. 1 2