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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.


Development process of COMODI. The development process involved five steps with several iterations. First, we used BiVeS to generate the differences between all subsequent model versions. Second, we converted the formal description of more than 10000 differences into human-readable descriptions. Third, we manually studied these descriptions and derived hypotheses and explanations for them. Fourth, we grouped the human-readable descriptions into sets of concepts and derived candidate terms for the ontology. Fifth, we aggregated and classified these terms and implemented the first version of the ontology in Protégé
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Fig1: Development process of COMODI. The development process involved five steps with several iterations. First, we used BiVeS to generate the differences between all subsequent model versions. Second, we converted the formal description of more than 10000 differences into human-readable descriptions. Third, we manually studied these descriptions and derived hypotheses and explanations for them. Fourth, we grouped the human-readable descriptions into sets of concepts and derived candidate terms for the ontology. Fifth, we aggregated and classified these terms and implemented the first version of the ontology in Protégé

Mentions: COMODI was developed based on a study of changes in versions of SBML and CellML models. The models were retrieved from the respective model repositories. More specifically, we started our investigation by manually analysing a predefined set of cell cycle models2 from BioModels [12]. We subsequently extended this set with randomly chosen models from both, BioModels and the Physiome Model Repository [13]. The single steps of development are summarised in Fig. 1 and explained in the following:


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)

Development process of COMODI. The development process involved five steps with several iterations. First, we used BiVeS to generate the differences between all subsequent model versions. Second, we converted the formal description of more than 10000 differences into human-readable descriptions. Third, we manually studied these descriptions and derived hypotheses and explanations for them. Fourth, we grouped the human-readable descriptions into sets of concepts and derived candidate terms for the ontology. Fifth, we aggregated and classified these terms and implemented the first version of the ontology in Protégé
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig1: Development process of COMODI. The development process involved five steps with several iterations. First, we used BiVeS to generate the differences between all subsequent model versions. Second, we converted the formal description of more than 10000 differences into human-readable descriptions. Third, we manually studied these descriptions and derived hypotheses and explanations for them. Fourth, we grouped the human-readable descriptions into sets of concepts and derived candidate terms for the ontology. Fifth, we aggregated and classified these terms and implemented the first version of the ontology in Protégé
Mentions: COMODI was developed based on a study of changes in versions of SBML and CellML models. The models were retrieved from the respective model repositories. More specifically, we started our investigation by manually analysing a predefined set of cell cycle models2 from BioModels [12]. We subsequently extended this set with randomly chosen models from both, BioModels and the Physiome Model Repository [13]. The single steps of development are summarised in Fig. 1 and explained in the following:

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.