Open Access Highly Accessed Methodology article

Systematic integration of experimental data and models in systems biology

Peter Li1*, Joseph O Dada2, Daniel Jameson23, Irena Spasic4, Neil Swainston23, Kathleen Carroll13, Warwick Dunn13, Farid Khan13, Naglis Malys35, Hanan L Messiha1, Evangelos Simeonidis36, Dieter Weichart13, Catherine Winder1, Jill Wishart35, David S Broomhead37, Carole A Goble2, Simon J Gaskell13, Douglas B Kell1, Hans V Westerhoff368, Pedro Mendes239 and Norman W Paton23

Author Affiliations

1 School of Chemistry, The University of Manchester, Manchester M13 9PL, UK

2 School of Computer Science, The University of Manchester, Manchester M13 9PL, UK

3 Manchester Centre for Integrative Systems Biology, The University of Manchester, Manchester M1 7DN, UK

4 School of Computer Science & Informatics, Cardiff University, Cardiff CF24 3AA, UK

5 Faculty of Life Sciences, The University of Manchester, Manchester M13 9PL, UK

6 School of Chemical Engineering and Analytical Science, The University of Manchester, Manchester M60 1QD, UK

7 School of Mathematics, The University of Manchester, Manchester M13 9PL, UK

8 Department of Molecular Cell Physiology, Vrije Universiteit, de Boelelaan 1085, 1081 HV Amsterdam, The Netherlands

9 Virginia Bioinformatics Institute, Virginia Tech, Washington Street 0477, Blacksburg, VA 24061, USA

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BMC Bioinformatics 2010, 11:582  doi:10.1186/1471-2105-11-582

Published: 29 November 2010



The behaviour of biological systems can be deduced from their mathematical models. However, multiple sources of data in diverse forms are required in the construction of a model in order to define its components and their biochemical reactions, and corresponding parameters. Automating the assembly and use of systems biology models is dependent upon data integration processes involving the interoperation of data and analytical resources.


Taverna workflows have been developed for the automated assembly of quantitative parameterised metabolic networks in the Systems Biology Markup Language (SBML). A SBML model is built in a systematic fashion by the workflows which starts with the construction of a qualitative network using data from a MIRIAM-compliant genome-scale model of yeast metabolism. This is followed by parameterisation of the SBML model with experimental data from two repositories, the SABIO-RK enzyme kinetics database and a database of quantitative experimental results. The models are then calibrated and simulated in workflows that call out to COPASIWS, the web service interface to the COPASI software application for analysing biochemical networks. These systems biology workflows were evaluated for their ability to construct a parameterised model of yeast glycolysis.


Distributed information about metabolic reactions that have been described to MIRIAM standards enables the automated assembly of quantitative systems biology models of metabolic networks based on user-defined criteria. Such data integration processes can be implemented as Taverna workflows to provide a rapid overview of the components and their relationships within a biochemical system.