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COMODI: an ontology to characterise differences in versions of computational models in biology.

Scharm M, Waltemath D, Mendes P, Wolkenhauer O - J Biomed Semantics (2016)

Bottom Line: The resulting set of concepts led us to define candidate terms for the ontology.Finally, COMODI is a step towards predicting how a change in a model influences the simulation results.COMODI is encoded in OWL.

View Article: PubMed Central - PubMed

Affiliation: Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany. martin.scharm@uni-rostock.de.

ABSTRACT

Background: Open 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.

Methods: We 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.

Results: We 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.

Conclusion: COMODI, 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/ .

No MeSH data available.


Structure of the COMODI ontology. Differences between computational models can be annotated with the Change term. Using the properties appliesTo, hasIntention, hasReason, and affects, the differences can be linked to the terms of the four major branches of COMODI: XmlEntity, Intention, Reason and Target. All arrows between terms within these five branches indicate an is-a relation, unless labelled otherwise
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Fig2: Structure of the COMODI ontology. Differences between computational models can be annotated with the Change term. Using the properties appliesTo, hasIntention, hasReason, and affects, the differences can be linked to the terms of the four major branches of COMODI: XmlEntity, Intention, Reason and Target. All arrows between terms within these five branches indicate an is-a relation, unless labelled otherwise

Mentions: COMODI is organised into four branches around the central concept Change: XmlEntity, Intention, Reason, Target (cf. Fig. 2). As a running example, we use the change of a parameter in an imaginary SBML model. We assume that the parameter changed from 0.5 to 0.8 in the new version of the SBML model.Fig. 2


COMODI: an ontology to characterise differences in versions of computational models in biology.

Scharm M, Waltemath D, Mendes P, Wolkenhauer O - J Biomed Semantics (2016)

Structure of the COMODI ontology. Differences between computational models can be annotated with the Change term. Using the properties appliesTo, hasIntention, hasReason, and affects, the differences can be linked to the terms of the four major branches of COMODI: XmlEntity, Intention, Reason and Target. All arrows between terms within these five branches indicate an is-a relation, unless labelled otherwise
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4940905&req=5

Fig2: Structure of the COMODI ontology. Differences between computational models can be annotated with the Change term. Using the properties appliesTo, hasIntention, hasReason, and affects, the differences can be linked to the terms of the four major branches of COMODI: XmlEntity, Intention, Reason and Target. All arrows between terms within these five branches indicate an is-a relation, unless labelled otherwise
Mentions: COMODI is organised into four branches around the central concept Change: XmlEntity, Intention, Reason, Target (cf. Fig. 2). As a running example, we use the change of a parameter in an imaginary SBML model. We assume that the parameter changed from 0.5 to 0.8 in the new version of the SBML model.Fig. 2

Bottom Line: The resulting set of concepts led us to define candidate terms for the ontology.Finally, COMODI is a step towards predicting how a change in a model influences the simulation results.COMODI is encoded in OWL.

View Article: PubMed Central - PubMed

Affiliation: Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany. martin.scharm@uni-rostock.de.

ABSTRACT

Background: Open 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.

Methods: We 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.

Results: We 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.

Conclusion: COMODI, 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/ .

No MeSH data available.