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

Overview of attention for article published in Journal of Biomedical Semantics, July 2016
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Title
COMODI: an ontology to characterise differences in versions of computational models in biology
Published in
Journal of Biomedical Semantics, July 2016
DOI 10.1186/s13326-016-0080-2
Pubmed ID
Authors

Martin Scharm, Dagmar Waltemath, Pedro Mendes, Olaf Wolkenhauer

Abstract

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. 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. 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. 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/ .

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 29%
Researcher 4 19%
Student > Master 3 14%
Student > Bachelor 2 10%
Professor 1 5%
Other 3 14%
Unknown 2 10%
Readers by discipline Count As %
Computer Science 5 24%
Engineering 4 19%
Unspecified 2 10%
Biochemistry, Genetics and Molecular Biology 1 5%
Business, Management and Accounting 1 5%
Other 5 24%
Unknown 3 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 December 2016.
All research outputs
#15,416,191
of 22,925,760 outputs
Outputs from Journal of Biomedical Semantics
#238
of 364 outputs
Outputs of similar age
#226,487
of 354,540 outputs
Outputs of similar age from Journal of Biomedical Semantics
#11
of 18 outputs
Altmetric has tracked 22,925,760 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 364 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 354,540 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.