  Graph transformation approaches have been successfully used to analyse and
design chemical and biological systems. Here we build on top of a DPO
framework, in which molecules are modelled as typed attributed graphs and
chemical reactions are modelled as graph transformations. Edges and vertexes
can be labelled with first-order terms, which can be used to encode, e.g.,
steric information of molecules. While targeted to chemical settings, the
computational framework is intended to be very generic and applicable to the
exploration of arbitrary spaces derived via iterative application of rewrite
rules, such as process calculi like Milner's {\pi}-calculus. To illustrate the
generality of the framework, we introduce EpiM: a tool for computing execution
spaces of {\pi}-calculus processes. EpiM encodes {\pi}-calculus processes as
typed attributed graphs and then exploits the existing DPO framework to compute
their dynamics in the form of graphs where nodes are {\pi}-calculus processes
and edges are reduction steps. EpiM takes advantage of the graph-based
representation and facilities offered by the framework, like efficient
isomorphism checking to prune the space without resorting to explicit
structural equivalences. EpiM is available as an online Python-based tool.
