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Condor-COPASI: high-throughput computing for biochemical networks

Edward Kent1, Stefan Hoops2 and Pedro Mendes23*

Author affiliations

1 Doctoral Training Centre in Integrative Systems Biology, Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK

2 Virginia Bioinformatics Institute, Virginia Tech, Washington St 0477, Blacksburg, VA 24061, USA

3 School of Computer Science, Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK

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Citation and License

BMC Systems Biology 2012, 6:91  doi:10.1186/1752-0509-6-91

Published: 26 July 2012



Mathematical modelling has become a standard technique to improve our understanding of complex biological systems. As models become larger and more complex, simulations and analyses require increasing amounts of computational power. Clusters of computers in a high-throughput computing environment can help to provide the resources required for computationally expensive model analysis. However, exploiting such a system can be difficult for users without the necessary expertise.


We present Condor-COPASI, a server-based software tool that integrates COPASI, a biological pathway simulation tool, with Condor, a high-throughput computing environment. Condor-COPASI provides a web-based interface, which makes it extremely easy for a user to run a number of model simulation and analysis tasks in parallel. Tasks are transparently split into smaller parts, and submitted for execution on a Condor pool. Result output is presented to the user in a number of formats, including tables and interactive graphical displays.


Condor-COPASI can effectively use a Condor high-throughput computing environment to provide significant gains in performance for a number of model simulation and analysis tasks. Condor-COPASI is free, open source software, released under the Artistic License 2.0, and is suitable for use by any institution with access to a Condor pool. Source code is freely available for download at webcite, along with full instructions on deployment and usage.

Systems biology; Computational modelling; High-throughput computing; Distributed computing; Simulation