Scharm Martin, Gebhardt Tom, Touré Vasundra, Bagnacani Andrea, Salehzadeh-Yazdi Ali, Wolkenhauer Olaf, Waltemath Dagmar
Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, 18051, Germany.
Department of Biology, Norwegian University of Science and Technology, Trondheim, 7491, Norway.
BMC Syst Biol. 2018 Apr 12;12(1):53. doi: 10.1186/s12918-018-0553-2.
A useful model is one that is being (re)used. The development of a successful model does not finish with its publication. During reuse, models are being modified, i.e. expanded, corrected, and refined. Even small changes in the encoding of a model can, however, significantly affect its interpretation. Our motivation for the present study is to identify changes in models and make them transparent and traceable.
We analysed 13734 models from BioModels Database and the Physiome Model Repository. For each model, we studied the frequencies and types of updates between its first and latest release. To demonstrate the impact of changes, we explored the history of a Repressilator model in BioModels Database.
We observed continuous updates in the majority of models. Surprisingly, even the early models are still being modified. We furthermore detected that many updates target annotations, which improves the information one can gain from models. To support the analysis of changes in model repositories we developed MoSt, an online tool for visualisations of changes in models. The scripts used to generate the data and figures for this study are available from GitHub https://github.com/binfalse/BiVeS-StatsGenerator and as a Docker image at https://hub.docker.com/r/binfalse/bives-statsgenerator/ . The website https://most.bio.informatik.uni-rostock.de/ provides interactive access to model versions and their evolutionary statistics.
The reuse of models is still impeded by a lack of trust and documentation. A detailed and transparent documentation of all aspects of the model, including its provenance, will improve this situation. Knowledge about a model's provenance can avoid the repetition of mistakes that others already faced. More insights are gained into how the system evolves from initial findings to a profound understanding. We argue that it is the responsibility of the maintainers of model repositories to offer transparent model provenance to their users.
一个有用的模型是正在被(重新)使用的模型。成功模型的开发并不随着其发表而结束。在重用过程中,模型会被修改,即扩展、修正和完善。然而,即使模型编码中的微小变化也可能显著影响其解释。我们开展本研究的动机是识别模型中的变化并使其透明且可追溯。
我们分析了来自生物模型数据库(BioModels Database)和生理组模型库(Physiome Model Repository)的13734个模型。对于每个模型,我们研究了其首次发布和最新发布之间更新的频率和类型。为了证明变化的影响,我们探究了生物模型数据库中一个阻遏物模型(Repressilator model)的历史。
我们观察到大多数模型都在持续更新。令人惊讶的是,即使是早期的模型仍在被修改。我们还检测到许多更新针对注释,这提高了人们从模型中获取的信息。为了支持对模型库中变化的分析,我们开发了MoSt,这是一个用于可视化模型变化的在线工具。用于生成本研究数据和图表的脚本可从GitHub(https://github.com/binfalse/BiVeS-StatsGenerator)获取,也可作为Docker镜像从https://hub.docker.com/r/binfalse/bives-statsgenerator/获取。网站https://most.bio.informatik.uni-rostock.de/提供对模型版本及其进化统计信息的交互式访问。
模型的重用仍然受到缺乏信任和文档的阻碍。对模型所有方面(包括其来源)进行详细且透明的记录将改善这种情况。了解模型的来源可以避免重复他人已经遇到的错误。对于系统如何从最初的发现发展到深入理解,我们有了更多的见解。我们认为,模型库的维护者有责任向其用户提供透明的模型来源。