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RunBioSimulations: an extensible web application that simulates a wide range of computational modeling frameworks, algorithms, and formats
Author(s) -
Bilal Shaikh,
Gnaneswara Marupilla,
Michael Wilson,
Michael L. Blinov,
Ion I. Moraru,
Jonathan R. Karr
Publication year - 2021
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkab411
Subject(s) - computer science , extensibility , variety (cybernetics) , range (aeronautics) , data science , web application , computational model , machine learning , data mining , distributed computing , software engineering , algorithm , artificial intelligence , world wide web , programming language , materials science , composite material
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.

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