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runBioSimulations: an extensible web application that simulates a wide range of computational modeling frameworks, algorithms, and formats

View ORCID ProfileBilal Shaikh, Gnaneswara Marupilla, View ORCID ProfileMike Wilson, View ORCID ProfileMichael L. Blinov, View ORCID ProfileIon I. Moraru, View ORCID ProfileJonathan R. Karr
doi: https://doi.org/10.1101/2021.03.05.433787
Bilal Shaikh
1Icahn Institute for Data Science and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1255 5th Avenue, Suite C2, New York, NY 10029, USA
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Gnaneswara Marupilla
2Center for Cell Analysis and Modeling, University of Connecticut School of Medicine, 263 Farmington Avenue, Farmington, CT 06030, USA
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Mike Wilson
2Center for Cell Analysis and Modeling, University of Connecticut School of Medicine, 263 Farmington Avenue, Farmington, CT 06030, USA
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Michael L. Blinov
2Center for Cell Analysis and Modeling, University of Connecticut School of Medicine, 263 Farmington Avenue, Farmington, CT 06030, USA
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Ion I. Moraru
2Center for Cell Analysis and Modeling, University of Connecticut School of Medicine, 263 Farmington Avenue, Farmington, CT 06030, USA
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  • For correspondence: karr@mssm.edu moraru@uchc.edu
Jonathan R. Karr
1Icahn Institute for Data Science and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1255 5th Avenue, Suite C2, New York, NY 10029, USA
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  • For correspondence: karr@mssm.edu moraru@uchc.edu
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ABSTRACT

Comprehensive, predictive computational models have significant potential for science, bioengineering, and medicine. One promising way to achieve more predictive models is to combine submodels of multiple subsystems. To capture the multiple scales of biology, these submodels will likely require multiple modeling frameworks and simulation algorithms. Several community resources are already available for working with many of these frameworks and algorithms. However, the variety and sheer number of these resources make it challenging to find and use appropriate tools for each model, especially for novice modelers and experimentalists. To make these resources easier to use, we developed runBioSimulations (https://run.biosimulations.org), a single web application for executing a broad range of models. runBioSimulations leverages community resources, including BioSimulators, a new open registry of simulation tools. These resources currently enable runBioSimulations to execute nine frameworks and 44 algorithms, and they make runBioSimulations extensible to additional frameworks and algorithms. runBioSimulations also provides features for sharing simulations and interactively visualizing their results. We anticipate that runBioSimulations will foster reproducibility, stimulate collaboration, and ultimately facilitate the creation of more predictive models.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://run.biosimulations.org

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted March 05, 2021.
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runBioSimulations: an extensible web application that simulates a wide range of computational modeling frameworks, algorithms, and formats
Bilal Shaikh, Gnaneswara Marupilla, Mike Wilson, Michael L. Blinov, Ion I. Moraru, Jonathan R. Karr
bioRxiv 2021.03.05.433787; doi: https://doi.org/10.1101/2021.03.05.433787
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runBioSimulations: an extensible web application that simulates a wide range of computational modeling frameworks, algorithms, and formats
Bilal Shaikh, Gnaneswara Marupilla, Mike Wilson, Michael L. Blinov, Ion I. Moraru, Jonathan R. Karr
bioRxiv 2021.03.05.433787; doi: https://doi.org/10.1101/2021.03.05.433787

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