Henkel, RonNovère, Nicolas LeWolkenhauer, OlafWaltemath, DagmarGoltz, UrsulaMagnor, MarcusAppelrath, Hans-JürgenMatthies, Herbert K.Balke, Wolf-TiloWolf, Lars2018-11-062018-11-062012978-3-88579-602-2https://dl.gi.de/handle/20.500.12116/17789Over the past years various databases in Life Sciences have been developed, among them databases to handle computational models of biological systems. Exchange formats that represent these models are typically XML- based; they encode models as networks. Models are published together with supplementary materials such as annotations, simulation experiment descriptions, or result sets. In consequence, not only model files need to be managed, but also the associated simulation setups, and highly linked meta-information. We discuss here the use of graph databases for model storage as they well reflect this interrelated nature. They can also enhance the integrated management of computational models and associated meta-information, as they handle connections between models, simulation descriptions and result data files, as well as external knowledge. This property enhances version control, retrieval and ranking, thereby resulting in improved model reuse and result reproducibility.enText/Conference Paper1617-5468