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dc.contributor.authorRodriguez-Garcia, Miguel Angel
dc.contributor.authorHoehndorf, Robert
dc.date.accessioned2020-07-05T08:41:36Z
dc.date.available2020-07-05T08:41:36Z
dc.date.issued2018
dc.identifier.citationRodríguez-García, M. Á., & Hoehndorf, R. (2018). Inferring ontology graph structures using OWL reasoning. Figshare. https://doi.org/10.6084/M9.FIGSHARE.C.3970353.V1
dc.identifier.doi10.6084/m9.figshare.c.3970353.v1
dc.identifier.urihttp://hdl.handle.net/10754/663989
dc.description.abstractAbstract Background Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies’ semantic content remains a challenge. Results We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies’ semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph . Conclusions Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.
dc.publisherfigshare
dc.subjectBiochemistry
dc.subjectGenetics
dc.subjectPharmacology
dc.subject69999 Biological Sciences not elsewhere classified
dc.subject80699 Information Systems not elsewhere classified
dc.subjectCancer
dc.subject110309 Infectious Diseases
dc.subjectPlant Biology
dc.titleInferring ontology graph structures using OWL reasoning
dc.typeDataset
dc.contributor.departmentBio-Ontology Research Group (BORG)
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
kaust.personRodriguez-Garcia, Miguel Angel
kaust.personHoehndorf, Robert
dc.relation.issupplementtoDOI:10.1186/s12859-017-1999-8
display.relations<b> Is Supplement To:</b><br/> <ul> <li><i>[Article]</i> <br/> Rodríguez-García MÁ, Hoehndorf R (2018) Inferring ontology graph structures using OWL reasoning. BMC Bioinformatics 19. Available: http://dx.doi.org/10.1186/s12859-017-1999-8.. DOI: <a href="https://doi.org/10.1186/s12859-017-1999-8" >10.1186/s12859-017-1999-8</a> HANDLE: <a href="http://hdl.handle.net/10754/626867">10754/626867</a></li></ul>


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