Sickle Cell Disease Ontology Working Group, The Sickle Cell Disease Ontology: enabling universal sickle cell-based knowledge representation.
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Date
2019
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Abstract
Sickle cell disease (SCD) is one of the most common monogenic diseases in humans with
multiple phenotypic expressions that can manifest as both acute and chronic complications. Although described more than a century ago, challenges in comprehensive disease
management and collaborative research on this disease are compounded by the complex
molecular and clinical phenotypes of SCD, environmental and psychosocial factors,
limited therapeutic options and ambiguous terminology. This ambiguous terminology
has hampered the integration and interoperability of existing SCD knowledge, and
SCD research translation. The SCD Ontology (SCDO), which is a community-driven
integrative and universal knowledge representation system for SCD, overcomes this
issue by providing a controlled vocabulary developed by a group of experts in both SCD
and ontology design. SCDO is the first and most comprehensive standardized humanand machine-readable resource that unambiguously represents terminology and concepts about SCD for researchers, patients and clinicians. It is built around the central
concept ‘hemoglobinopathy’, allowing inclusion of non-SCD haemoglobinopathies, such
as thalassaemias, which may interfere with or influence SCD phenotypic manifestations. This collaboratively developed ontology constitutes a comprehensive knowledge
management system and standardized terminology of various SCD-related factors. The
SCDO will promote interoperability of different research datasets, facilitate seamless
data sharing and collaborations, including meta-analyses within the SCD community,
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Keywords
The Sickle Cell, Ontology, Disease
Citation
Adekile, A., Anie, K.A., Hamda, C.B., Brown, B., Bukini, D., Campbell, A., Chaouch, M., Chimusa, E., Chunda-Liyoka, C., Dennis-Antwi, J. and Derebail, V.K., 2019. The Sickle Cell Disease Ontology: enabling universal sickle cell-based knowledge representation. Database, 2019.