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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 architecture. The inner circle represents the OPPL wrapper and the outer one Galaxy. Galaxy manages the data and parameters that will be passed to the OPPL wrapper. In order to pass, for instance, an ontology to the OPPL wrapper, the ontology must be first uploaded to Galaxy (or passed to it from the output of another Galaxy tool). Also, Galaxy manages the output of the OPPL wrapper: it can be redirected to other Galaxy tools or downloaded and saved as a standalone file. The OPPL wrapper coordinates the OPPL API (to parse the OPPL script and execute it), the OWL API (to read/write ontologies from stdin/to stdout and perform changes), and the chosen reasoner (to perform inferences).
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Figure 3: OPPL-Galaxy architecture. The inner circle represents the OPPL wrapper and the outer one Galaxy. Galaxy manages the data and parameters that will be passed to the OPPL wrapper. In order to pass, for instance, an ontology to the OPPL wrapper, the ontology must be first uploaded to Galaxy (or passed to it from the output of another Galaxy tool). Also, Galaxy manages the output of the OPPL wrapper: it can be redirected to other Galaxy tools or downloaded and saved as a standalone file. The OPPL wrapper coordinates the OPPL API (to parse the OPPL script and execute it), the OWL API (to read/write ontologies from stdin/to stdout and perform changes), and the chosen reasoner (to perform inferences).

Mentions: OPPL can be executed through the graphical interface of Protégé [27] and Populous. Despite those possible means of manipulating ontologies, OPPL cannot be used as part of a workflow, limiting the possibilities of including other bioinformatics analysis tools, unless a tailored Java program is written using the OPPL API. OPPL-Galaxy fills that gap by offering an enhanced version of OPPL that can be used in combination with other Galaxy tools. To that end, an OPPL wrapper was developed as a mediator between Galaxy and both the OPPL 2 API [28] and the OWL API [29] (Figure 3).


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 architecture. The inner circle represents the OPPL wrapper and the outer one Galaxy. Galaxy manages the data and parameters that will be passed to the OPPL wrapper. In order to pass, for instance, an ontology to the OPPL wrapper, the ontology must be first uploaded to Galaxy (or passed to it from the output of another Galaxy tool). Also, Galaxy manages the output of the OPPL wrapper: it can be redirected to other Galaxy tools or downloaded and saved as a standalone file. The OPPL wrapper coordinates the OPPL API (to parse the OPPL script and execute it), the OWL API (to read/write ontologies from stdin/to stdout and perform changes), and the chosen reasoner (to perform inferences).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 3: OPPL-Galaxy architecture. The inner circle represents the OPPL wrapper and the outer one Galaxy. Galaxy manages the data and parameters that will be passed to the OPPL wrapper. In order to pass, for instance, an ontology to the OPPL wrapper, the ontology must be first uploaded to Galaxy (or passed to it from the output of another Galaxy tool). Also, Galaxy manages the output of the OPPL wrapper: it can be redirected to other Galaxy tools or downloaded and saved as a standalone file. The OPPL wrapper coordinates the OPPL API (to parse the OPPL script and execute it), the OWL API (to read/write ontologies from stdin/to stdout and perform changes), and the chosen reasoner (to perform inferences).
Mentions: OPPL can be executed through the graphical interface of Protégé [27] and Populous. Despite those possible means of manipulating ontologies, OPPL cannot be used as part of a workflow, limiting the possibilities of including other bioinformatics analysis tools, unless a tailored Java program is written using the OPPL API. OPPL-Galaxy fills that gap by offering an enhanced version of OPPL that can be used in combination with other Galaxy tools. To that end, an OPPL wrapper was developed as a mediator between Galaxy and both the OPPL 2 API [28] and the OWL API [29] (Figure 3).

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.