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  4. The Epilepsy Ontology: a community-based ontology tailored for semantic interoperability and text mining
 
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2023
Journal Article
Title

The Epilepsy Ontology: a community-based ontology tailored for semantic interoperability and text mining

Abstract
Motivation: Epilepsy is a multifaceted complex disorder that requires a precise understanding of the classification, diagnosis, treatment and disease mechanism governing it. Although scattered resources are available on epilepsy, comprehensive and structured knowledge is missing. In contemplation to promote multidisciplinary knowledge exchange and facilitate advancement in clinical management, especially in pre-clinical research, a disease-specific ontology is necessary. The presented ontology is designed to enable better interconnection between scientific community members in the epilepsy domain.
Results: The Epilepsy Ontology (EPIO) is an assembly of structured knowledge on various aspects of epilepsy, developed according to Basic Formal Ontology (BFO) and Open Biological and Biomedical Ontology (OBO) Foundry principles. Concepts and definitions are collected from the latest International League against Epilepsy (ILAE) classification, domain-specific ontologies and scientific literature. This ontology consists of 1879 classes and 28 151 axioms (2171 declaration axioms, 2219 logical axioms) from several aspects of epilepsy. This ontology is intended to be used for data management and text mining purposes.
Availability and implementation: The current release of the ontology is publicly available under a Creative Commons 4.0 License and shared via http://purl.obolibrary.org/obo/epso.owl and is a community-based effort assembling various facets of the complex disease. The ontology is also deposited in BioPortal at https://bioportal.bio ontology.org/ontologies/EPIO.
Author(s)
Sargsyan, Astghik  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Wegner, Philipp
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Gebel, Stephan
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Kaladharan, Abish
Sethumadhavan, Priya
Lage-Rupprecht, Vanessa
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Darms, Johannes
Schultz, Bruce  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Klein, Jürgen
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Jacobs, Marc  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Madan, Sumit  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Hofmann-Apitius, Martin  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Tom Kodamullil, Alpha
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Journal
Bioinformatics advances  
Open Access
DOI
10.1093/bioadv/vbad033
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