Combining computational models, semantic annotations, and associated simulation experiments in a graph database

Model repositories such as the BioModels Database or the CellML Model Repository are frequently accessed to retrieve computational models describing biological systems. However, the current designs of these databases limit the types of supported queries, and many data in these repositories cannot easily be accessed. Computational methods for model retrieval cannot be applied. In this paper we present a storage concept that meets this challenge. It grounds on a graph database, reflects the models' structure, incorporates semantic annotations and experiment 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 such as network structure.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, filtering etc.We exemplify how CellML- and SBML-encoded models can be maintained in one database, how these models can be linked via annotations, and queried.