title: Annotation-based feature extraction from sets of SBML models.
abstract: BACKGROUND
  Model repositories such as BioModels Database provide computational models of biological systems for the scientific community. These models contain rich semantic annotations that link model entities to concepts in well-established bio-ontologies such as Gene Ontology. Consequently, thematically similar models are likely to share similar annotations. Based on this assumption, we argue that semantic annotations are a suitable tool to characterize sets of models. These characteristics improve model classification, allow to identify additional features for model retrieval tasks, and enable the comparison of sets of models.
  
  
  RESULTS
  In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in SBML format which were composed from BioModels Database. To characterize each of these sets, we analyzed and extracted concepts from three frequently used ontologies, namely Gene Ontology, ChEBI and SBO. We find that three out of the methods are suitable to determine characteristic features for arbitrary sets of models: The selected features vary depending on the underlying model set, and they are also specific to the chosen model set. We show that the identified features map on concepts that are higher up in the hierarchy of the ontologies than the concepts used for model annotations. Our analysis also reveals that the information content of concepts in ontologies and their usage for model annotation do not correlate.
  
  
  CONCLUSIONS
  Annotation-based feature extraction enables the comparison of model sets, as opposed to existing methods for model-to-keyword comparison, or model-to-model comparison.
authors.affiliation: Department of Multimedia Communication, University of Rostock, Joachim-Jungius-Str. 11, Rostock, 18051 Germany ; Fraunhofer Institute for Computer Graphics Research IGD, Joachim-Jungius-Str. 11, Rostock, 18059 Germany.
authors.forename: Rebekka
authors.initials: R
authors.lastname: Alm
authors.affiliation: Department of Systems Biology and Bioinformatics, University of Rostock, Ulmenstr. 69, Rostock, 18051 Germany.
authors.forename: Dagmar
authors.initials: D
authors.lastname: Waltemath
authors.affiliation: Department of Systems Biology and Bioinformatics, University of Rostock, Ulmenstr. 69, Rostock, 18051 Germany.
authors.forename: Markus
authors.initials: M
authors.lastname: Wolfien
authors.affiliation: Department of Systems Biology and Bioinformatics, University of Rostock, Ulmenstr. 69, Rostock, 18051 Germany ; Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, South Africa.
authors.forename: Olaf
authors.initials: O
authors.lastname: Wolkenhauer
authors.affiliation: Department of Mobile Multimedia Information Systems, University of Rostock, Albert-Einstein-Str. 22, Rostock, 18051 Germany.
authors.forename: Ron
authors.initials: R
authors.lastname: Henkel
keywords: Bio-ontologies; Feature extraction; Model similarity; SBML