ArticleJournal of biomedical semantics2016
COMODI: an ontology to characterise differences in versions of computational models in biology.
Article in Journal of biomedical semantics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Article
- SBML Level 3: an extensible format for the exchange and reuse of biological models.Molecular systems biology · 2020Review
- Harmonizing semantic annotations for computational models in biology.Briefings in bioinformatics · 2019Review
- ModelBricks-modules for reproducible modeling improving model annotation and provenance.NPJ systems biology and applications · 2019Review
- Data Management in Computational Systems Biology: Exploring Standards, Tools, Databases, and Packaging Best Practices.Methods in molecular biology (Clifton, N.J.) · 2019Article
- Evolution of computational models in BioModels Database and the Physiome Model Repository.BMC systems biology · 2018Article
- Notions of similarity for systems biology models.Briefings in bioinformatics · 2018Article
- Identifying frequent patterns in biochemical reaction networks: a workflow.Database : the journal of biological databases and curation · 2018Article
- Analyzing structural changes in SNOMED CT's Bacterial infectious diseases using a visual semantic delta.Journal of biomedical informatics · 2017Article
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4 authors.
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Abstract
backgroundOpen model repositories provide ready-to-reuse computational models of biological systems. Models within those repositories evolve over time, leading to different model versions. Taken together, the underlying changes reflect a model's provenance and thus can give valuable insights into the studied biology. Currently, however, changes cannot be semantically interpreted. To improve this situation, we developed an ontology of terms describing changes in models. The ontology can be used by scientists and within software to characterise model updates at the level of single changes. When studying or reusing a model, these annotations help with determining the relevance of a change in a given context.
methodsWe manually studied changes in selected models from BioModels and the Physiome Model Repository. Using the BiVeS tool for difference detection, we then performed an automatic analysis of changes in all models published in these repositories. The resulting set of concepts led us to define candidate terms for the ontology. In a final step, we aggregated and classified these terms and built the first version of the ontology.
resultsWe present COMODI, an ontology needed because COmputational MOdels DIffer. It empowers users and software to describe changes in a model on the semantic level. COMODI also enables software to implement user-specific filter options for the display of model changes. Finally, COMODI is a step towards predicting how a change in a model influences the simulation results.
conclusionCOMODI, coupled with our algorithm for difference detection, ensures the transparency of a model's evolution, and it enhances the traceability of updates and error corrections. COMODI is encoded in OWL. It is openly available at http://comodi.sems.uni-rostock.de/ .
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