The simulation experiment description markup language (SED-ML): language specification for level 1 version 4.
The simulation experiment description markup language (SED-ML): language specification for level 1 version 4.
复制标题
模拟实验说明标记语言（SED-ML）：1级版本4的语言规范。
DOI：
10.1515/jib-2021-0021
复制
发表时间：
2021-10-05
影响因子：
1.9
通讯作者：
König M
中科院分区：
文献类型：
--
作者：
Smith LP;Bergmann FT;Garny A;Helikar T;Karr J;Nickerson D;Sauro H;Waltemath D;König M
计算模拟实验越来越多地为现代生物学研究提供信息，并带来了提供注释、存档、共享和复制实验的方法的需求。这些模拟越来越需要建模者、实验家和工程师之间的广泛合作。关于模拟实验的最小信息（MIASE）指南概述了共享模拟实验所需的信息。SED-ML是MIASE概述的信息的计算机可读格式，作为一个社区项目创建，并得到许多研究人员和软件工具的支持。第一个版本的SED-ML侧重于模型的确定性和随机模拟。Level 1版本4的SED-ML实质上扩展了这些功能，以涵盖其他类型的模型、模型语言、参数估计、模型的仿真和分析，以及仿真结果的分析和可视化。为了促进整个社区的一致实践，Level 1 Version 4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由不断增长的研究人员、模型语言和软件工具的生态系统支持，包括八种基于约束的、动态的、定性的、基于规则的和空间模型的语言，超过20种仿真工具、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/。
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/.