About Bio-PEPA

Bio-PEPA is a language for the modelling and the analysis of biochemical networks.

It is based on PEPA, a process algebra originally defined for the performance analysis of computer systems, and extends it in order to handle some features of biochemical networks, such as stoichiometry and different kinds of kinetic laws. A main feature of Bio-PEPA is the possibility to support different kinds of analysis, from stochastic simulation to analysis based on ordinary differential equations (ODEs), to model checking in PRISM.

You can find a detailed description of the language in the following paper:

Bio-PEPA: a Framework for the Modelling and Analysis of Biochemical Networks.
F. Ciocchetta and J. Hillston.
To appear in Theoretical Computer Science.
Preliminary version.

Main features

The main features of Bio-PEPA are:
  • it offers a formal abstraction of biochemical networks, composed of a set of biochemical species that interact each other through some reactions;

  • It supports general kinds of kinetic laws and expresses them as functional rates;

  • It supports the definition of stoichiometry and the information about the role of the species (reactant, product, enzyme, ...);

  • It is defined in terms of a syntax and a (structural operational) semantics. There are species components, to represent biochemical species, and model components, to express how species components cooperate with each other. The model component contains the initial/current concentration of each species. In addition to these components, a Bio-PEPA system is composed of the set of compartments, the set of functional rates, the set of constant parameters and auxiliary information for the analysis. For details see here

  • A stochastic labelled transition system can de derived from the semantics. Differently from other process algebras, each (species) component is associated with a discrete level of concentration. We assume a finite maximum concentration and, given a concentration step size H, we obtain a number of levels for the species. The step size is assumed equal for all the species in a given compartment and represents the granularity of the system. The smaller H is, the finer the granularity. For details see here

  • The view in terms of levels is reflected to the CTMC derived from the stochastic labelled transition system. We call these Markov Chains CTMC with levels. For details see here.

  • A Bio-PEPA system is a formal, intermediate and compositional representation of biochemical systems, on which different kinds of analysis can be carried out. The idea underlining Bio-PEPA is represented in the following schema:

    Each of these kinds of analysis can be of help for studying different aspects of the biological model. Moreover, they can be used in conjunction in order to have a better understanding of the system.

An illustrative example

In order to see how we can model a biochemical network into Bio-PEPA


Recently, some extensions of Bio-PEPA have been defined in order to represent some specific features of some biochemical networks. Specifically, we have:
  • Bio-PEPA with SBML-events. This extension has been defined in order to handle events, constructs that represent changes in the system due to some trigger conditions. This allows us to represent the possible change to the system, due, for instance, to the introduction of some reagents or the interruption of some external stimuli. The language is mapped to Hybrid Automata (HA), a formalism that consider both continuous and discrete changes. for details see here.

  • Bio-PEPA with biological compartments. The language is extended with some features in order to represent more details about locations of species and reactions. Locations can represent either compartments or membranes. A hierarchy of location is considered to represent the relation between them and the transition labels are enriched with some information about locations. Compartments have a fixed structure, but their size can depend on time. For details see here.


The Bio-PEPA project has been supported by:

  • the CODA project (Process Algebra Approaches for Collective Dynamics), founded by the EPSRC, reference EP/c54370x/01 and ARF EP/c543696/01

  • the Signal Project (Stochastic process algebra for biochemical signalling pathway analysis), funded by EPSRC, reference EP/E031439/1

  • the Centre for Systems Biology at Edinburgh (CSBE), a Centre for Integrative Systems Biology (CISB) funded by BBSRC and EPSRC, reference BB/D019621/1.