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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-Galaxy Web interface. The OPPL-Galaxy Web interface is displayed in the middle pane. In the left pane, a list of standard Galaxy tools is shown; in the right pane, a sample of a history of the executed tasks is shown.
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Figure 4: OPPL-Galaxy Web interface. The OPPL-Galaxy Web interface is displayed in the middle pane. In the left pane, a list of standard Galaxy tools is shown; in the right pane, a sample of a history of the executed tasks is shown.

Mentions: OPPL-Galaxy takes as input a target ontology and an OPPL script: both artefacts are uploaded to Galaxy by the user or produced as output by another Galaxy tool. It generates a new ontology that has been changed according to the instructions defined in the OPPL script, thus axioms are added or removed. The OPPL-Galaxy Web interface presents the following options (Figure 4):


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-Galaxy Web interface. The OPPL-Galaxy Web interface is displayed in the middle pane. In the left pane, a list of standard Galaxy tools is shown; in the right pane, a sample of a history of the executed tasks is shown.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 4: OPPL-Galaxy Web interface. The OPPL-Galaxy Web interface is displayed in the middle pane. In the left pane, a list of standard Galaxy tools is shown; in the right pane, a sample of a history of the executed tasks is shown.
Mentions: OPPL-Galaxy takes as input a target ontology and an OPPL script: both artefacts are uploaded to Galaxy by the user or produced as output by another Galaxy tool. It generates a new ontology that has been changed according to the instructions defined in the OPPL script, thus axioms are added or removed. The OPPL-Galaxy Web interface presents the following options (Figure 4):

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.