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Briefings in Bioinformatics Advance Access published online on June 23, 2008
Briefings in Bioinformatics, doi:10.1093/bib/bbn026
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© The Author 2008. Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org

A structured approach for the engineering of biochemical network models, illustrated for signalling pathways

Rainer Breitling, David Gilbert, Monika Heiner and Richard Orton

Corresponding author. David Gilbert, Bioinformatics Research Centre, University of Glasgow, Glasgow G12 8QQ, Scotland, UK. Tel: +44 141 330 2563; Fax: +44 141 330 8627; E-mail: drg{at}dcs.gla.ac.uk

Quantitative models of biochemical networks (signal transduction cascades, metabolic pathways, gene regulatory circuits) are a central component of modern systems biology. Building and managing these complex models is a major challenge that can benefit from the application of formal methods adopted from theoretical computing science. Here we provide a general introduction to the field of formal modelling, which emphasizes the intuitive biochemical basis of the modelling process, but is also accessible for an audience with a background in computing science and/or model engineering. We show how signal transduction cascades can be modelled in a modular fashion, using both a qualitative approach—qualitative Petri nets, and quantitative approaches—continuous Petri nets and ordinary differential equations (ODEs). We review the major elementary building blocks of a cellular signalling model, discuss which critical design decisions have to be made during model building, and present a number of novel computational tools that can help to explore alternative modular models in an easy and intuitive manner. These tools, which are based on Petri net theory, offer convenient ways of composing hierarchical ODE models, and permit a qualitative analysis of their behaviour. We illustrate the central concepts using signal transduction as our main example. The ultimate aim is to introduce a general approach that provides the foundations for a structured formal engineering of large-scale models of biochemical networks.

Keywords: systems biology, biochemical networks, modelling, signal transduction, Petri nets, ordinary differential equations

Submitted: March 20, 2008. Received (in revised form): May 2, 2008.


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