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Bioinformatics. 2019 May 1;35(9):1600-1602. doi: 10.1093/bioinformatics/bty829.

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

Author information

1
Seattle Children's Research Institute, Center for Global Infectious Disease Research, Seattle, WA, USA.
2
Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA.
3
Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.

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.

PMID:
30256901
PMCID:
PMC6499248
[Available on 2020-05-01]
DOI:
10.1093/bioinformatics/bty829

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