ONTO-PERL: An API for supporting the development and analysis of bio-ontologies

Bioinformatics, Mar 2008

Motivation: Many biomedical ontologies use OBO or OWL as knowledge representation language. The rapid increase of such ontologies calls for adequate tools to facilitate their use. In particular, there is a pressing need to programmatically deal with such ontologies in many applications, including data integration, text mining, as well as semantic applications supporting translational research. Results: We present an Application Programming Interface (API) called ONTO-PERL. This API significantly extends the repertoire of available tools supporting the development and analysis of bio-ontologies. Availability: The source code code as well as sample usage scripts can be found at: http://search.cpan.org/dist/ONTO-PERL/ Contact: erick.antezana{at}psb.ugent.be

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ONTO-PERL: An API for supporting the development and analysis of bio-ontologies

Erick Antezana 1 2 Mikel Egan a 0 Bernard De Baets 3 Martin Kuiper 1 2 Vladimir Mironov 1 2 Associate Editor: Alex Bateman 0 University of Manchester, School of Computer Science , Oxford Road, M13 9PL Manchester, UK 1 Department of Molecular Genetics, Ghent University , Technologiepark 927, 9052 Gent, Belgium 2 Department of Plant Systems Biology , VIB 3 Department of Applied Mathematics , Biometrics and Process Control, Ghent University , Computer links 653, 9000 Gent, Belgium Motivation: Many biomedical ontologies use OBO or OWL as knowledge representation language. The rapid increase of such ontologies calls for adequate tools to facilitate their use. In particular, there is a pressing need to programmatically deal with such ontologies in many applications, including data integration, text mining, as well as semantic applications supporting translational research. Results: We present an Application Programming Interface (API) called ONTO-PERL. This API significantly extends the repertoire of available tools supporting the development and analysis of bioontologies. Availability: The source code code as well as sample usage scripts can be found at: http://search.cpan.org/dist/ONTO-PERL/ Contact: - INTRODUCTION Ontologies support consistent and unambiguous knowledge sharing and provide a framework for knowledge integration. More specifically, ontologies represent the agreed knowledge about a domain of discourse. The knowledge is represented by creating a single model with the terms of the domain as well as the relationships between those terms (Stevens et al., 2007). The relationships between terms effectively define what properties a given term must have. Entities are also linked to human readable information like labels. Thus, an ontology links term labels to their interpretations, i.e. specifications of their meanings, defined as a set of properties. As such, ontologies can be used to support automatic semantic interpretation of textual information, thereby providing a basis for advanced text mining (Doms et al., 2005; Mu ller et al., 2004). Moreover, structured and integrated knowledge provides a basis for advanced reasoning to validate hypotheses and generate new knowledge (Blake et al., 2006; Myhre et al., 2006). Reasoning services can be used to re-engineer the design of parts of the whole ontology (such as classification) or to design entirely new extensions that comply with the current knowledge *To whom correspondence should be addressed. (Wolstencroft et al., 2007). All these scenarios and applications need foundational tools to deal with ontologies. OBO1 and OWL2 are becoming the de facto knowledge representation languages in the biomedical domain. OBO is human readable and it has gained wide acceptance. Many ontologies, such as GO (The Gene Ontology Consortium, 2000), are expressed in OBO. However, OBO does not have an explicit and well-defined semantics. In contrast, OWL is computer readable since it does have such a semantics, and, hence, automated reasoning can be performed on OWL ontologies. Several tools are currently available to manage and develop OBO and OWL ontologies, either in the form of ontology editors or APIs. Within the bio-ontology community, OBOEdit Day-Richter07 (OBO-centered) and Prote ge 3 (OWLcentered) are the most frequently used ontology-building environments. Prote g e also has a plug-in for loading OBO ontologies (Moreira et al., 2007). Both ontology editors offer open java APIs that can be used to build applications and explore bio-ontologies. There also exist some independent APIs (or API-like tools) in java and perl. In java, OWL or OBO ontologies can be loaded and managed with the OWL API.4 In PERL, go-perl,5 GO::Term::Finder (Boyle et al., 2004) and Bio::Ontology6 are available. go-perl and GO::Term::Finder are GO-specific, and therefore many bio-ontologies, such as those under the OBO foundry,7 cannot be handled easily without tweaking the code. Bio::Ontology is not GO-specific but it lacks important functionalities, for instance, to intersect two ontologies, unify ontologies, export to different formats (OWL, XML, DOT, etc). Moreover, it lacks modularity in annotations (such as def, synonym and dbxref). Therefore, we present ONTO-PERL, an OBO-centered PERL API that provides a turnkey service to help bio-ontologists handle ontologies, do data exploration and perform mining. 1http://www.geneontology.org/GO.format.obo-1_2.shtml 2http://www.w3.org/TR/owl-features/ 3http://protege.stanford.edu/ 4http://owlapi.sourceforge.net/ 5http://amigo.geneontology.org/dev/go-perl/doc/go-perl-doc.html 6http://search.cpan.org/dist/bioperl/ 7http://obofoundry.org/ Fig. 1. Simplified object model of ONTO-PERL. 2 IMPLEMENTATION ONTO-PERL comprises an extensible set of object-oriented PERL modules that can be used for programmatically working with ontologies. ONTO-PERL can be installed as any typical CPAN module.8 A set of comprehensive test files is included in the distributi (...truncated)


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Erick Antezana, Mikel Egaña, Bernard De Baets, Martin Kuiper, Vladimir Mironov. ONTO-PERL: An API for supporting the development and analysis of bio-ontologies, Bioinformatics, 2008, pp. 885-887, 24/6, DOI: 10.1093/bioinformatics/btn042