{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["6"],"submitter":["Alm R"],"pubmed_abstract":["<h4>Background</h4>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.<h4>Results</h4>In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in S"],"journal":["Journal of biomedical semantics"],"pagination":["20"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC4405863"],"repository":["biostudies-literature"],"pubmed_title":["Annotation-based feature extraction from sets of SBML models."],"pmcid":["PMC4405863"],"pubmed_authors":["Henkel R","Alm R","Wolkenhauer O","Wolfien M","Waltemath D"],"additional_accession":[]},"is_claimable":false,"name":"Annotation-based feature extraction from sets of SBML models.","description":"<h4>Background</h4>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.<h4>Results</h4>In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in S","dates":{"release":"2015-01-01T00:00:00Z","publication":"2015","modification":"2025-04-18T15:04:21.46Z","creation":"2019-03-27T01:50:19Z"},"accession":"S-EPMC4405863","cross_references":{"pubmed":["25904997"],"doi":["10.1186/s13326-015-0014-4"]}}