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OnEX: Exploring changes in life science ontologies.

Hartung M, Kirsten T, Gross A, Rahm E - BMC Bioinformatics (2009)

Bottom Line: The system is based on a three-tier architecture including an ontology version repository, a middleware component and the OnEX web application.Interactive workflows allow a systematic and explorative change analysis of ontologies and their concepts as well as the semi-automatic migration of out-dated annotations to the current version of an ontology.OnEX provides a user-friendly web interface to explore information about changes in current life science ontologies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Interdisciplinary Centre for Bioinformatics, University of Leipzig, Härtelstrasse 16-18, 04107 Leipzig, Germany. hartung@izbi.uni-leipzig.de

ABSTRACT

Background: Numerous ontologies have recently been developed in life sciences to support a consistent annotation of biological objects, such as genes or proteins. These ontologies underlie continuous changes which can impact existing annotations. Therefore, it is valuable for users of ontologies to study the stability of ontologies and to see how many and what kind of ontology changes occurred.

Results: We present OnEX (Ontology Evolution EXplorer) a system for exploring ontology changes. Currently, OnEX provides access to about 560 versions of 16 well-known life science ontologies. The system is based on a three-tier architecture including an ontology version repository, a middleware component and the OnEX web application. Interactive workflows allow a systematic and explorative change analysis of ontologies and their concepts as well as the semi-automatic migration of out-dated annotations to the current version of an ontology.

Conclusion: OnEX provides a user-friendly web interface to explore information about changes in current life science ontologies. It is available at http://www.izbi.de/onex.

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Concept-based analysis workflow. Parts of the concept-based analysis workflow.
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Figure 4: Concept-based analysis workflow. Parts of the concept-based analysis workflow.

Mentions: The scenario in Figure 4 illustrates the concept-based evolution analysis for blood coagulation concepts across all ontologies. We first use a string-based keyword search for the expression blood coagulation (Search Panel) delivering Search Results, i.e., matching terms in the selected ontologies. In the example we obtain 7 matches for the GO BP sub-ontology and further matches in two other ontologies. The user may now select a matched term of interest to inspect its history in more detail (here GO:0007596 – blood coagulation of GO BP). The resulting Concept Evolution panel has two parts. The first part provides information about the concept in the latest version (name, accession number, definition, synonyms, obsolete status, parents and children) and some historical statistics (creation date or periods of non-existence). The second part presents the history of the concept in tabular form. The table indicates the initial status (attribute values, relationships) of a concept at creation time and lists all concept changes such as additions, modifications or deletions of attribute values and relationships. For instance, the blood coagulation concept has been introduced in December 2002 and was available in all versions until now. Parent relationships to GO:0007599 (hemostasis), GO:0050817 (coagulation) and GO:0042060 (wound healing) were added between 2003 and 2005. Other changes affected the synonyms, for example the expression blood clotting was temporarily deleted and blood coagulation factor activity was only present between 2005 and 2007.


OnEX: Exploring changes in life science ontologies.

Hartung M, Kirsten T, Gross A, Rahm E - BMC Bioinformatics (2009)

Concept-based analysis workflow. Parts of the concept-based analysis workflow.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2746816&req=5

Figure 4: Concept-based analysis workflow. Parts of the concept-based analysis workflow.
Mentions: The scenario in Figure 4 illustrates the concept-based evolution analysis for blood coagulation concepts across all ontologies. We first use a string-based keyword search for the expression blood coagulation (Search Panel) delivering Search Results, i.e., matching terms in the selected ontologies. In the example we obtain 7 matches for the GO BP sub-ontology and further matches in two other ontologies. The user may now select a matched term of interest to inspect its history in more detail (here GO:0007596 – blood coagulation of GO BP). The resulting Concept Evolution panel has two parts. The first part provides information about the concept in the latest version (name, accession number, definition, synonyms, obsolete status, parents and children) and some historical statistics (creation date or periods of non-existence). The second part presents the history of the concept in tabular form. The table indicates the initial status (attribute values, relationships) of a concept at creation time and lists all concept changes such as additions, modifications or deletions of attribute values and relationships. For instance, the blood coagulation concept has been introduced in December 2002 and was available in all versions until now. Parent relationships to GO:0007599 (hemostasis), GO:0050817 (coagulation) and GO:0042060 (wound healing) were added between 2003 and 2005. Other changes affected the synonyms, for example the expression blood clotting was temporarily deleted and blood coagulation factor activity was only present between 2005 and 2007.

Bottom Line: The system is based on a three-tier architecture including an ontology version repository, a middleware component and the OnEX web application.Interactive workflows allow a systematic and explorative change analysis of ontologies and their concepts as well as the semi-automatic migration of out-dated annotations to the current version of an ontology.OnEX provides a user-friendly web interface to explore information about changes in current life science ontologies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Interdisciplinary Centre for Bioinformatics, University of Leipzig, Härtelstrasse 16-18, 04107 Leipzig, Germany. hartung@izbi.uni-leipzig.de

ABSTRACT

Background: Numerous ontologies have recently been developed in life sciences to support a consistent annotation of biological objects, such as genes or proteins. These ontologies underlie continuous changes which can impact existing annotations. Therefore, it is valuable for users of ontologies to study the stability of ontologies and to see how many and what kind of ontology changes occurred.

Results: We present OnEX (Ontology Evolution EXplorer) a system for exploring ontology changes. Currently, OnEX provides access to about 560 versions of 16 well-known life science ontologies. The system is based on a three-tier architecture including an ontology version repository, a middleware component and the OnEX web application. Interactive workflows allow a systematic and explorative change analysis of ontologies and their concepts as well as the semi-automatic migration of out-dated annotations to the current version of an ontology.

Conclusion: OnEX provides a user-friendly web interface to explore information about changes in current life science ontologies. It is available at http://www.izbi.de/onex.

Show MeSH