Xu Jin, Smith Lucian
Department of Bioengineering, University of Washington, Seattle, WA, United States of America.
PLoS One. 2024 Dec 5;19(12):e0314875. doi: 10.1371/journal.pone.0314875. eCollection 2024.
The reproducibility of computational biology models can be greatly facilitated by widely adopted standards and public repositories. We examined 50 models from the BioModels Database and attempted to validate the original curation and correct some of them if necessary. For each model, we reproduced these published results using Tellurium. Once reproduced we manually created a new set of files, with the model information stored by the Systems Biology Markup Language (SBML), and simulation instructions stored by the Simulation Experiment Description Markup Language (SED-ML), and everything included in an Open Modeling EXchange (OMEX) file, which could be used with a variety of simulators to reproduce the same results. On the one hand, the reproducibility procedure of 50 models developed a manual workflow that we would use to build an automatic platform to help users more easily curate and verify models in the future. On the other hand, these exercises allowed us to find the limitations and possible enhancement of the current curation and tooling to verify and curate models.
广泛采用的标准和公共知识库能够极大地促进计算生物学模型的可重复性。我们检查了来自生物模型数据库的50个模型,并尝试验证原始编目,必要时对其中一些进行修正。对于每个模型,我们使用Tellurium重现这些已发表的结果。一旦重现,我们手动创建了一组新文件,其中模型信息由系统生物学标记语言(SBML)存储,模拟指令由模拟实验描述标记语言(SED-ML)存储,所有内容都包含在一个开放建模交换(OMEX)文件中,该文件可与各种模拟器一起使用以重现相同的结果。一方面,50个模型的可重复性过程开发了一种手动工作流程,我们将使用该流程构建一个自动平台,以帮助用户在未来更轻松地策划和验证模型。另一方面,这些实践使我们能够发现当前模型验证和策划的编目及工具的局限性和可能的改进之处。