SemGen: a tool for semantics-based annotation and composition of biosimulation models

Abstract

Summary: As the number and complexity of biosimulation models grows, so do demands for tools that can help users understand models and compose more comprehensive and accurate systems from existing models. SemGen is a tool for semantics-based annotation and composition of biosimulation models designed to address this demand. A key SemGen capability is to decompose and then integrate models across existing model exchange formats including SBML and CellML. To support this capability, we use semantic annotations to explicitly capture the underlying biological and physical meanings of the entities and processes that are modeled. SemGen leverages annotations to expose a model's biological and computational architecture and to help automate model composition.

Availability and implementation: SemGen is freely available at https://github.com/SemBioProcess/SemGen.

Supplementary information: Supplementary data are available at Bioinformatics online.

Fig. 1.

Visualizing coupling points during model merging. When performing merging tasks such as the one described in the text, SemGen can illustrate the coupling points between the computational dependency networks of the merged models. The four non-directional lines in the center of the image connect model variables that have the same biological meaning. For example, the variables ‘Kapela.Ca_i’ and ‘c’ both represent cytosolic calcium concentration. Other lines indicate computational dependencies between variables. Inset shows full SemGen interface; dashed box indicates area of detail