ArticleBMC systems biology2012
Condor-COPASI: high-throughput computing for biochemical networks.
Article in BMC systems biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Molecular Resonance Identification in Complex Absorbing Potentials via Integrated Quantum Computing and High-Throughput Computing.Journal of chemical theory and computation · 2026Article
- Kiphynet: an online network simulation tool connecting cellular kinetics and physiological transport.Metabolomics : Official journal of the Metabolomic Society · 2024Article
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- A pathway model of glucose-stimulated insulin secretion in the pancreaticFrontiers in endocrinology · 2023Article
- Reproducibility and FAIR principles: the case of a segment polarity network model.Frontiers in cell and developmental biology · 2023Article
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- Data Management and Modeling in Plant Biology.Frontiers in plant science · 2021Review
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- Multisite rate control analysis identifies ribosomal scanning as the sole high-capacity/low-flux-control step in mRNA translation.The FEBS journal · 2020Article
- PyCoTools: a Python toolbox for COPASI.Bioinformatics (Oxford, England) · 2018Article
- SBpipe: a collection of pipelines for automating repetitive simulation and analysis tasks.BMC systems biology · 2017Article
- Metabolic regulation is sufficient for global and robust coordination of glucose uptake, catabolism, energy production and growth in Escherichia coli.PLoS computational biology · 2017Article
- Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy.BMC bioinformatics · 2017Article
- PASMet: a web-based platform for prediction, modelling and analyses of metabolic systems.Nucleic acids research · 2016Article
- Modeling the Role of Lanthionine Synthetase C-Like 2 (LANCL2) in the Modulation of Immune Responses to Helicobacter pylori Infection.PloS one · 2016Article
- Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery.Drug discovery today · 2014Review
- Mechanisms of regulation of olfactory transduction and adaptation in the olfactory cilium.PloS one · 2014Article
- cuTauLeaping: a GPU-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems.PloS one · 2014Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundMathematical 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.
resultsWe 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.
conclusionsCondor-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 http://code.google.com/p/condor-copasi/, along with full instructions on deployment and usage.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.