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2016 ; 7
(ä): 38
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DermO; an ontology for the description of dermatologic disease
#MMPMID27296450
Fisher HM
; Hoehndorf R
; Bazelato BS
; Dadras SS
; King LE Jr
; Gkoutos GV
; Sundberg JP
; Schofield PN
J Biomed Semantics
2016[Jun]; 7
(ä): 38
PMID27296450
show ga
BACKGROUND: There have been repeated initiatives to produce standard nosologies
and terminologies for cutaneous disease, some dedicated to the domain and some
part of bigger terminologies such as ICD-10. Recently, formally structured
terminologies, ontologies, have been widely developed in many areas of biomedical
research. Primarily, these address the aim of providing comprehensive working
terminologies for domains of knowledge, but because of the knowledge contained in
the relationships between terms they can also be used computationally for many
purposes. RESULTS: We have developed an ontology of cutaneous disease,
constructed manually by domain experts. With more than 3000 terms, DermO
represents the most comprehensive formal dermatological disease terminology
available. The disease entities are categorized in 20 upper level terms, which
use a variety of features such as anatomical location, heritability, affected
cell or tissue type, or etiology, as the features for classification, in line
with professional practice and nosology in dermatology. Available in OBO flatfile
and OWL 2 formats, it is integrated semantically with other ontologies and
terminologies describing diseases and phenotypes. We demonstrate the application
of DermO to text mining the biomedical literature and in the creation of a
network describing the phenotypic relationships between cutaneous diseases.
CONCLUSIONS: DermO is an ontology with broad coverage of the domain of
dermatologic disease and we demonstrate here its utility for text mining and
investigation of phenotypic relationships between dermatologic disorders. We
envision that in the future it may be applied to the creation and mining of
electronic health records, clinical training and basic research, as it supports
automated inference and reasoning, and for the broader integration of skin
disease information with that from other domains.