Alzheimer's disease; Alzheimer's disease ontology; Neurodegeneration; Neurodegenerative diseases; Ontology; Semantic Web; Computational Biology; Humans; Alzheimer Disease; Information Storage and Retrieval; Models, Biological; Epidemiology; Health Policy; Developmental Neuroscience; Neurology (clinical); Geriatrics and Gerontology; Cellular and Molecular Neuroscience; Psychiatry and Mental Health
Abstract :
[en] BACKGROUND: Biomedical ontologies offer the capability to structure and represent domain-specific knowledge semantically. Disease-specific ontologies can facilitate knowledge exchange across multiple disciplines, and ontology-driven mining approaches can generate great value for modeling disease mechanisms. However, in the case of neurodegenerative diseases such as Alzheimer's disease, there is a lack of formal representation of the relevant knowledge domain.
METHODS: Alzheimer's disease ontology (ADO) is constructed in accordance to the ontology building life cycle. The Protégé OWL editor was used as a tool for building ADO in Ontology Web Language format.
RESULTS: ADO was developed with the purpose of containing information relevant to four main biological views-preclinical, clinical, etiological, and molecular/cellular mechanisms-and was enriched by adding synonyms and references. Validation of the lexicalized ontology by means of named entity recognition-based methods showed a satisfactory performance (F score = 72%). In addition to structural and functional evaluation, a clinical expert in the field performed a manual evaluation and curation of ADO. Through integration of ADO into an information retrieval environment, we show that the ontology supports semantic search in scientific text. The usefulness of ADO is authenticated by dedicated use case scenarios.
CONCLUSIONS: Development of ADO as an open ADO is a first attempt to organize information related to Alzheimer's disease in a formalized, structured manner. We demonstrate that ADO is able to capture both established and scattered knowledge existing in scientific text.
Disciplines :
Neurology
Author, co-author :
Malhotra, Ashutosh; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin, Germany, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn-Aachen International Center for IT, Bonn, Germany
Younesi, Erfan; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin, Germany, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn-Aachen International Center for IT, Bonn, Germany
Gündel, Michaela; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin, Germany
Müller, Bernd; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin, Germany
HENEKA, Michael ; Department of Neurology, Clinical Neurosciences Unit, University of Bonn, Bonn, Germany
Hofmann-Apitius, Martin; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin, Germany, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn-Aachen International Center for IT, Bonn, Germany. Electronic address: martin.hofmann-apitius@scai.fraunhofer.de
External co-authors :
yes
Language :
English
Title :
ADO: a disease ontology representing the domain knowledge specific to Alzheimer's disease.
Publication date :
March 2014
Journal title :
Alzheimer's and Dementia: the Journal of the Alzheimer's Association
We thank Dr. Michael Krams at Johnson & Johnson for his contribution to the provision of the competency queries, Theo Mevissen, Harsha Gurulingappa for technical support, and Stephan Springstubbe for fruitful discussions and motivational support during the project. This work was supported by the Bonn-Aachen International Center for Information Technology foundation and a scholarship to A. M. (ScholarShip PLUS program of the State of NorthRhineWestfalen).
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