University of Washington, Seattle, USA.
BioQUANT/COS, Heidelberg University, Heidelberg, Germany.
J Integr Bioinform. 2021 Oct 5;18(3):20210021. doi: 10.1515/jib-2021-0021.
Computational simulation experiments increasingly inform modern biological research, and bring with them the need to provide ways to annotate, archive, share and reproduce the experiments performed. These simulations increasingly require extensive collaboration among modelers, experimentalists, and engineers. The Minimum Information About a Simulation Experiment (MIASE) guidelines outline the information needed to share simulation experiments. SED-ML is a computer-readable format for the information outlined by MIASE, created as a community project and supported by many investigators and software tools. The first versions of SED-ML focused on deterministic and stochastic simulations of models. Level 1 Version 4 of SED-ML substantially expands these capabilities to cover additional types of models, model languages, parameter estimations, simulations and analyses of models, and analyses and visualizations of simulation results. To facilitate consistent practices across the community, Level 1 Version 4 also more clearly describes the use of SED-ML constructs, and includes numerous concrete validation rules. SED-ML is supported by a growing ecosystem of investigators, model languages, and software tools, including eight languages for constraint-based, kinetic, qualitative, rule-based, and spatial models, over 20 simulation tools, visual editors, model repositories, and validators. Additional information about SED-ML is available at https://sed-ml.org/.
计算模拟实验越来越多地为现代生物学研究提供信息，并需要提供注释、存档、共享和重现所进行实验的方法。这些模拟实验越来越需要建模者、实验人员和工程师之间的广泛合作。模拟实验信息最低要求（Minimum Information About a Simulation Experiment，MIASE）指南概述了共享模拟实验所需的信息。SED-ML 是一种计算机可读的格式，用于表示 MIASE 概述的信息，它是作为一个社区项目创建的，并得到了许多研究人员和软件工具的支持。SED-ML 的最初版本专注于模型的确定性和随机模拟。SED-ML 第 1 版第 4 级大大扩展了这些功能，以涵盖其他类型的模型、模型语言、参数估计、模型模拟和分析，以及模拟结果的分析和可视化。为了在整个社区中促进一致的实践，第 1 版第 4 级还更清楚地描述了 SED-ML 结构的使用，并包含了许多具体的验证规则。SED-ML 得到了越来越多的研究人员、模型语言和软件工具的支持，包括用于基于约束、动力学、定性、基于规则和空间模型的八种语言，超过 20 种模拟工具、可视化编辑器、模型存储库和验证器。有关 SED-ML 的更多信息，请访问 https://sed-ml.org/。
