Henkel Ron, Wolkenhauer Olaf, Waltemath Dagmar
University of Rostock, Department of Computer Science, Albert-Einstein-Straße 22, D-18059 Rostock, Germany, Department of Systems Biology and Bioinformatics, University of Rostock, Ulmenstrasse 69, 18057 Rostock, Germany and Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch 7600, South Africa
University of Rostock, Department of Computer Science, Albert-Einstein-Straße 22, D-18059 Rostock, Germany, Department of Systems Biology and Bioinformatics, University of Rostock, Ulmenstrasse 69, 18057 Rostock, Germany and Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch 7600, South Africa University of Rostock, Department of Computer Science, Albert-Einstein-Straße 22, D-18059 Rostock, Germany, Department of Systems Biology and Bioinformatics, University of Rostock, Ulmenstrasse 69, 18057 Rostock, Germany and Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch 7600, South Africa.
Database (Oxford). 2015 Mar 8;2015. doi: 10.1093/database/bau130. Print 2015.
Model repositories such as the BioModels Database, the CellML Model Repository or JWS Online are frequently accessed to retrieve computational models of biological systems. However, their storage concepts support only restricted types of queries and not all data inside the repositories can be retrieved. In this article we present a storage concept that meets this challenge. It grounds on a graph database, reflects the models' structure, incorporates semantic annotations and simulation descriptions and ultimately connects different types of model-related data. The connections between heterogeneous model-related data and bio-ontologies enable efficient search via biological facts and grant access to new model features. The introduced concept notably improves the access of computational models and associated simulations in a model repository. This has positive effects on tasks such as model search, retrieval, ranking, matching and filtering. Furthermore, our work for the first time enables CellML- and Systems Biology Markup Language-encoded models to be effectively maintained in one database. We show how these models can be linked via annotations and queried. Database URL: https://sems.uni-rostock.de/projects/masymos/
诸如生物模型数据库、CellML模型库或JWS Online等模型存储库经常被访问以检索生物系统的计算模型。然而，它们的存储概念仅支持有限类型的查询，并且存储库中的所有数据并非都能被检索到。在本文中，我们提出了一种应对这一挑战的存储概念。它基于图数据库，反映模型结构，纳入语义注释和模拟描述，并最终连接不同类型的与模型相关的数据。异构的与模型相关的数据和生物本体之间的连接使得能够通过生物学事实进行高效搜索，并能访问新的模型特征。所引入的概念显著改善了模型存储库中计算模型及相关模拟的访问。这对模型搜索、检索、排名、匹配和筛选等任务产生积极影响。此外，我们的工作首次使以CellML和系统生物学标记语言编码的模型能够在一个数据库中得到有效维护。我们展示了这些模型如何通过注释进行链接和查询。数据库网址：https://sems.uni-rostock.de/projects/masymos/
