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OPPL-Galaxy, a Galaxy tool for enhancing ontology exploitation as part of bioinformatics workflows.

Aranguren ME, Fernández-Breis JT, Mungall C, Antezana E, González AR, Wilkinson MD - J Biomed Semantics (2013)

Bottom Line: Use cases are provided in order to demonstrate OPPL-Galaxy's capability for enriching, modifying and querying biomedical ontologies.Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts.OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses.

View Article: PubMed Central - HTML - PubMed

Affiliation: Ontology Engineering Group, School of Computer Science, Technical University of Madrid (UPM), Boadilla del Monte, 28660, Spain. mikel.egana.aranguren@upm.es.

ABSTRACT

Background: Biomedical ontologies are key elements for building up the Life Sciences Semantic Web. Reusing and building biomedical ontologies requires flexible and versatile tools to manipulate them efficiently, in particular for enriching their axiomatic content. The Ontology Pre Processor Language (OPPL) is an OWL-based language for automating the changes to be performed in an ontology. OPPL augments the ontologists' toolbox by providing a more efficient, and less error-prone, mechanism for enriching a biomedical ontology than that obtained by a manual treatment.

Results: We present OPPL-Galaxy, a wrapper for using OPPL within Galaxy. The functionality delivered by OPPL (i.e. automated ontology manipulation) can be combined with the tools and workflows devised within the Galaxy framework, resulting in an enhancement of OPPL. Use cases are provided in order to demonstrate OPPL-Galaxy's capability for enriching, modifying and querying biomedical ontologies.

Conclusions: Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts. OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses.

No MeSH data available.


OPPL pipeline. The OPPL engine takes an ontology (circle group on the left) and an OPPL script (dotted square) as inputs, and performs the changes defined by the OPPL script on the input ontology, thereby generating a new output ontology (modified ontology, on the right).
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Figure 2: OPPL pipeline. The OPPL engine takes an ontology (circle group on the left) and an OPPL script (dotted square) as inputs, and performs the changes defined by the OPPL script on the input ontology, thereby generating a new output ontology (modified ontology, on the right).

Mentions: The actions are based on the addition or removal of axioms of any complexity to/from entities retrieved by the query (OWL classes, properties, or instances). Once an OPPL script has been defined, the OPPL engine is passed this script and the ontology to be modified. The OPPL engine, in turn, modifies the ontology according to the changes defined in the OPPL script, generating a new ontology (Figures 1 and 2).


OPPL-Galaxy, a Galaxy tool for enhancing ontology exploitation as part of bioinformatics workflows.

Aranguren ME, Fernández-Breis JT, Mungall C, Antezana E, González AR, Wilkinson MD - J Biomed Semantics (2013)

OPPL pipeline. The OPPL engine takes an ontology (circle group on the left) and an OPPL script (dotted square) as inputs, and performs the changes defined by the OPPL script on the input ontology, thereby generating a new output ontology (modified ontology, on the right).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3643862&req=5

Figure 2: OPPL pipeline. The OPPL engine takes an ontology (circle group on the left) and an OPPL script (dotted square) as inputs, and performs the changes defined by the OPPL script on the input ontology, thereby generating a new output ontology (modified ontology, on the right).
Mentions: The actions are based on the addition or removal of axioms of any complexity to/from entities retrieved by the query (OWL classes, properties, or instances). Once an OPPL script has been defined, the OPPL engine is passed this script and the ontology to be modified. The OPPL engine, in turn, modifies the ontology according to the changes defined in the OPPL script, generating a new ontology (Figures 1 and 2).

Bottom Line: Use cases are provided in order to demonstrate OPPL-Galaxy's capability for enriching, modifying and querying biomedical ontologies.Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts.OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses.

View Article: PubMed Central - HTML - PubMed

Affiliation: Ontology Engineering Group, School of Computer Science, Technical University of Madrid (UPM), Boadilla del Monte, 28660, Spain. mikel.egana.aranguren@upm.es.

ABSTRACT

Background: Biomedical ontologies are key elements for building up the Life Sciences Semantic Web. Reusing and building biomedical ontologies requires flexible and versatile tools to manipulate them efficiently, in particular for enriching their axiomatic content. The Ontology Pre Processor Language (OPPL) is an OWL-based language for automating the changes to be performed in an ontology. OPPL augments the ontologists' toolbox by providing a more efficient, and less error-prone, mechanism for enriching a biomedical ontology than that obtained by a manual treatment.

Results: We present OPPL-Galaxy, a wrapper for using OPPL within Galaxy. The functionality delivered by OPPL (i.e. automated ontology manipulation) can be combined with the tools and workflows devised within the Galaxy framework, resulting in an enhancement of OPPL. Use cases are provided in order to demonstrate OPPL-Galaxy's capability for enriching, modifying and querying biomedical ontologies.

Conclusions: Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts. OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses.

No MeSH data available.