We introduce a natural language interface for building stochastic pi 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
demonstrate the language on a model of Fc-gamma receptor phosphorylation during
phagocytosis. We provide a tool implementation of the translation into a
stochastic pi calculus language, Microsoft Research's SPiM