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运行生物模拟:一个可扩展的网络应用程序,可模拟各种计算建模框架、算法和格式。

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

作者信息

Shaikh Bilal, Marupilla Gnaneswara, Wilson Mike, Blinov Michael L, Moraru Ion I, Karr Jonathan R

机构信息

Icahn Institute for Data Science & Genomic Technology and Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029, USA.

Center for Cell Analysis and Modeling, University of Connecticut School of Medicine, 263 Farmington Avenue, Farmington, CT 06030, USA.

出版信息

Nucleic Acids Res. 2021 Jul 2;49(W1):W597-W602. doi: 10.1093/nar/gkab411.

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.

摘要

全面的预测性计算模型在科学、生物工程和医学领域具有巨大潜力。实现更具预测性模型的一种有前景的方法是将多个子系统的子模型结合起来。为了捕捉生物学的多个尺度,这些子模型可能需要多种建模框架和模拟算法。已经有一些社区资源可用于使用其中许多框架和算法。然而,这些资源的多样性和数量之多使得为每个模型找到并使用合适的工具具有挑战性,尤其是对于新手建模者和实验人员。为了使这些资源更易于使用,我们开发了RunBioSimulations(https://run.biosimulations.org),这是一个用于执行广泛模型的单一网络应用程序。RunBioSimulations利用了社区资源,包括BioSimulators,这是一个新的模拟工具开放注册表。这些资源目前使RunBioSimulations能够执行九个框架和44种算法,并且使RunBioSimulations可扩展到其他框架和算法。RunBioSimulations还提供了用于共享模拟和交互式可视化其结果的功能。我们预计RunBioSimulations将促进可重复性,激发合作,并最终促进创建更多预测性模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eaa7/8262693/fd3ad2c849e4/gkab411gra1.jpg

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