Integrating systems biology models and biomedical ontologies
2011

Integrating Systems Biology Models and Biomedical Ontologies

Sample size: 269 publication Evidence: high

Author Information

Author(s): Robert Hoehndorf, Michel Dumontier, John H. Gennari, Sarala Wimalaratne, Bernard de Bono, Daniel L. Cook, Georgios V. Gkoutos

Hypothesis

Can we integrate representations of in silico systems biology with those of in vivo biology using biomedical ontologies?

Conclusion

The integration of annotated biosimulation models and biomedical ontologies enables the verification of models and expressive queries.

Supporting Evidence

  • The SBML Harvester software was developed to facilitate the integration of systems biology models with biomedical ontologies.
  • 269 computational models from the BioModels Database were converted and analyzed.
  • The integration allows for complex biological queries that span multiple domains.
  • Automated reasoning was used to verify the biological consistency of models.
  • Contradictions were detected in 27 models due to annotation issues.
  • The framework demonstrates potential for large-scale analyses of biological systems.
  • Ontologies provide a means to bridge levels of granularity in biological data.
  • The method enhances the accessibility and understanding of biosimulation models.

Takeaway

This study shows how to connect computer models of biological systems with real-life biology to help scientists ask better questions and verify their models.

Methodology

The study developed the SBML Harvester software to convert annotated SBML models into OWL and applied it to models in the BioModels Database.

Limitations

The method relies on the availability of ontology-based annotations for systems biology resources.

Digital Object Identifier (DOI)

10.1186/1752-0509-5-124

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