DermO; an ontology for the description of dermatologic disease.
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.
Dept. of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK.
Hannah M
HM
Fisher
Computational Bioscience Research Center, King Abdullah University of Science and Technology, 23955-6900, Thuwal, Kingdom of Saudi Arabia.
Robert
R
Hoehndorf
Dept. of Computer Science, Llandinam Building, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DB, UK.
Bruno S
BS
Bazelato
Dept. Dermatology and Pathology, University of Connecticut Health Center, 263, Farmington Avenue, Farmington, CT, 06030, USA.
Soheil S
SS
Dadras
Dept. of Medicine, Div. Dermatology, Vanderbilt University, Nashville, Tennessee, USA.
Lloyd E
LE
King
Dept. of Computer Science, Llandinam Building, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DB, UK.|College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, B15 2TT, UK.|Institute of Translational Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham, B15 2TT, UK.
Georgios V
GV
Gkoutos
The Jackson Laboratory, 600, Main Street, Bar Harbor Maine, ME 04609-1500, USA.
John P
JP
Sundberg
Dept. of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK. pns12@cam.ac.uk.|The Jackson Laboratory, 600, Main Street, Bar Harbor Maine, ME 04609-1500, USA. pns12@cam.ac.uk.
Paul N
PN
Schofield
D064229:Biological Ontologies; D057225:Data Mining; D006801:Humans; D020407:Internet; D011642:Publications; D012871:Skin Diseases
Dermatology; Dermatopathology; Disease; Ontology