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    Inferring ontology graph structures using OWL reasoning

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    Type
    Dataset
    Authors
    Rodriguez-Garcia, Miguel Angel cc
    Hoehndorf, Robert cc
    KAUST Department
    Bio-Ontology Research Group (BORG)
    Computational Bioscience Research Center (CBRC)
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2018
    Permanent link to this record
    http://hdl.handle.net/10754/663989
    
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    Abstract
    Abstract 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.
    Citation
    Rodríguez-García, M. Á., & Hoehndorf, R. (2018). Inferring ontology graph structures using OWL reasoning. Figshare. https://doi.org/10.6084/M9.FIGSHARE.C.3970353.V1
    Publisher
    figshare
    DOI
    10.6084/m9.figshare.c.3970353.v1
    Relations
    Is Supplement To:
    • [Article]
      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: 10.1186/s12859-017-1999-8 HANDLE: 10754/626867
    ae974a485f413a2113503eed53cd6c53
    10.6084/m9.figshare.c.3970353.v1
    Scopus Count
    Collections
    Bio-Ontology Research Group (BORG); Computer Science Program; Computational Bioscience Research Center (CBRC); Datasets; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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