Proceedings of the 2009 Winter Simulation Conference
M. D. Rossetti, R. R. Hill, B. Johansson, A. Dunkin, and R. G. Ingalls, eds.
DESIGN AND DEVELOPMENT OF SOFTWARE TOOLS FOR BIO-PEPA
Adam Duguid
Stephen Gilmore
Maria Luisa Guerriero
School of Informatics
The University of Edinburgh
Edinburgh, EH8 9AB, U.K.
Jane Hillston
Laurence Loewe
Centre for Systems Biology at Edinburgh
The University of Edinburgh
Edinburgh, EH9 3JH, U.K.
ABSTRACT
This paper surveys the design of software tools for the Bio-PEPA process algebra. Bio-PEPA is a high-level language for
modelling biological systems such as metabolic pathways and other biochemical reaction networks. Through providing tools
for this modelling language we hope to allow easier use of a range of simulators and model-checkers thereby freeing the
modeller from the responsibility of developing a custom simulator for the problem of interest. Further, by providing mappings
to a range of different analysis tools the Bio-PEPA language allows modellers to compare analysis results which have been
computed using independent numerical analysers, which enhances the reliability and robustness of the results computed.
1 INTRODUCTION
Systems biology has recently inspired much work on simulation tools and techniques (Kitano 2002). It was born with the
realisation that computational models are pivotal for understanding the increasingly complex molecular biological systems
under investigation (Regev and Shapiro 2002). Such models can make quantitative predictions, which improve our capacity
to construct falsifiable hypotheses that are at the heart of scientific progress. The need for quantitative models in biology is
enormous and will further increase as the quantitative approach of systems biology slowly works its way into various other
biological disciplines. For example, evolutionary systems biology depends on the ability to automatically analyse variations
in many realistic models for answering some of the most difficult questions in evolutionary biology (Loewe 2009). To meet
this need for high quality simulations, it is desirable to have an easy way of building concise models of biochemical reaction
networks. It is also desirable that these models are amenable to as many automated model analysis techniques as possible.
This contributes to the quality of results and to the level of understanding without requiring potentially large amounts of
time for tedious and error-prone low-level programming tasks.
The goal of Bio-PEPA tools is to deliver a modelling environment that is easy to use and supports a wide range of
analyses for biochemical systems. Such systems consist of biochemical species which are affected by reactions that change
the numbers of these species. Bio-PEPA (Ciocchetta and Hillston 2008, Ciocchetta and Hillston 2009) is a stochastic process
algebra designed specifically for investigating these systems. It represents species of molecules as “sequential components”
and reactions as “actions” (for simplicity, we will continue to call them “species” and “reactions” here). Bio-PEPA supports
various qualitative analysis methods in addition to quantitative methods such as discrete stochastic simulation, continuous
deterministic simulation, and probabilistic model-checking. The Bio-PEPA language promotes integrated model analysis
where a high-level language (in our case a process algebra) is mapped to a set of different model representations so that a
range of different formal analyses can be applied. This has been demonstrated in a number of examples (Calder et al. 2006,
Ciocchetta et al. 2009).
The Bio-PEPA tools are under constant development to support language extensions and new analysis techniques.
For instance, following the recent formal definitions of locations (Ciocchetta and Guerriero 2009) and events (Ciocchetta
2009), their support within the Bio-PEPA tools is currently under development. Furthermore, novel analysis techniques and
abstractions for Bio-PEPA (for instance the application of behavioural equivalences (Galpin and Hillston 2009)), can be
easily integrated into the Bio-PEPA tools.
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