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

Martin Scharm; Dagmar Waltemath; Pedro Mendes; Olaf Wolkenhauer

doi:10.7287/peerj.preprints.1857v1

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

Martin Scharm ¹, Dagmar Waltemath¹, Pedro Mendes^2,3, Olaf Wolkenhauer^1,4

1 Dept. of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany

2 School of Computer Science and Manchester Institute of Biotechnology, University of Manchester, Manchester, United Kingdom

3 Center for Quantitative Medicine, University of Connecticut, Farmington, CT, USA

4 Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, South Africa

DOI: 10.7287/peerj.preprints.1857v1

Published: 2016-03-13
Accepted: 2016-03-13

Subject Areas: Biochemistry, Cell Biology, Computational Biology, Computational Science
Keywords: ontology, modelling, difference detection, SBML, CellML

Copyright: © 2016 Scharm et al.
Licence: This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.

Cite this article: Scharm M, Waltemath D, Mendes P, Wolkenhauer O. 2016. COMODI: An ontology to characterise differences in versions of computational models in biology. PeerJ Preprints 4:e1857v1 https://doi.org/10.7287/peerj.preprints.1857v1

Abstract

Motivation: Open model repositories provide ready-to-reuse computational models of biological systems. Models within those repositories evolve over time, leading to many alternative and subsequent 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 computational biology 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 the next step towards predicting how a change in a model influences the simulation study.

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.

Availability: COMODI is encoded in OWL. It is openly available at http://comodi.sems.uni-rostock.de/.