Simulation Foundry: Automated and F.A.I.R. Molecular Modeling.,Journal of Chemical Information and Modeling

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Simulation Foundry: Automated and F.A.I.R. Molecular Modeling.
Journal of Chemical Information and Modeling ( IF 5.6 ) Pub Date : 2020-04-02 , DOI: 10.1021/acs.jcim.0c00018
Gudrun Gygli ₁ , Juergen Pleiss ₁

Affiliation

The Simulation Foundry (SF) is a modular workflow for the automated creation of molecular modeling (MM) data. MM allows for the reliable prediction of the microscopic and macroscopic properties of multicomponent systems from first principles. The SF makes MM repeatable, replicable, and findable, accessible, interoperable, and reusable (F.A.I.R.). The SF uses a standardized data structure and file naming convention, allowing for replication on different supercomputers and re-entrancy. We focus on keeping the SF simple by basing it on scripting languages that are widely used by the MM community (bash, Python) and making it reusable and re-editable. The SF was developed to assist expert users in performing parameter studies of multicomponent systems by high throughput molecular dynamics simulations. The usability of the SF is demonstrated by simulations of thermophysical properties of binary mixtures. A standardized data exchange format enables the integration of simulated data with data from experiments. The SF also provides a complete documentation of how the results were obtained, thus assigning provenance. Increasing computational power facilitates the intensification of the simulation process and requires automation and modularity. The SF provides a community platform on which to integrate new methods and create data that is reproducible and transparent (https://fairdomhub.org/studies/639/snapshots/1, https://fairdomhub.org/studies/639/snapshots/2).

中文翻译：

模拟铸造厂：自动化和公平的分子建模。

Simulation Foundry（SF）是用于自动创建分子建模（MM）数据的模块化工作流程。MM允许根据第一原理可靠地预测多组分系统的微观和宏观特性。SF使MM可重复，可复制和可找到，可访问，可互操作且可重用（FAIR）。SF使用标准化的数据结构和文件命名约定，从而允许在不同的超级计算机上进行复制并重新输入。我们致力于通过基于MM社区（bash，Python）广泛使用的脚本语言并使其可重用和可编辑来使SF保持简单。SF的开发旨在通过高通量分子动力学模拟帮助专家用户进行多组分系统的参数研究。SF的可用性通过对二元混合物的热物理性质进行仿真来证明。标准化的数据交换格式可以将模拟数据与实验数据集成在一起。SF还提供了有关如何获得结果的完整文档，从而指定了来源。计算能力的提高促进了仿真过程的加强，并需要自动化和模块化。SF提供了一个社区平台，在该平台上可以集成新方法并创建可重复且透明的数据（https://fairdomhub.org/studies/639/snapshots/1、https://fairdomhub.org/studies/639/snapshots / 2）。SF还提供了有关如何获得结果的完整文档，从而指定了来源。计算能力的提高促进了仿真过程的加强，并需要自动化和模块化。SF提供了一个社区平台，在该平台上可以集成新方法并创建可重复且透明的数据（https://fairdomhub.org/studies/639/snapshots/1、https://fairdomhub.org/studies/639/snapshots / 2）。SF还提供了有关如何获得结果的完整文档，从而指定了来源。计算能力的提高促进了仿真过程的加强，并需要自动化和模块化。SF提供了一个社区平台，在该平台上可以集成新方法并创建可重复且透明的数据（https://fairdomhub.org/studies/639/snapshots/1、https://fairdomhub.org/studies/639/snapshots / 2）。

更新日期：2020-04-02

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