AuthorsFisher, Hannah M.
Bazelato, Bruno S.
Dadras, Soheil S.
King, Lloyd E.
Gkoutos, Georgios V.
Sundberg, John P.
Schofield, Paul N.
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Permanent link to this recordhttp://hdl.handle.net/10754/614411
MetadataShow full item record
AbstractBackground 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.
CitationDermO; an ontology for the description of dermatologic disease 2016, 7 (1) Journal of Biomedical Semantics
SponsorsThe authors acknowledge National Institutes of Health Grants R21-AR063781 to JPS and SSD, and R01HG004838-03 supported PNS and GVG. We thank Prof. Jonathan Bard for helpful comments on the manuscript and Prof. Amanda Oakley, for the support of DermNet NZ.
JournalJournal of Biomedical Semantics
- Generating a focused view of disease ontology cancer terms for pan-cancer data integration and analysis.
- Authors: Wu TJ, Schriml LM, Chen QR, Colbert M, Crichton DJ, Finney R, Hu Y, Kibbe WA, Kincaid H, Meerzaman D, Mitraka E, Pan Y, Smith KM, Srivastava S, Ward S, Yan C, Mazumder R
- Issue date: 2015
- MicrO: an ontology of phenotypic and metabolic characters, assays, and culture media found in prokaryotic taxonomic descriptions.
- Authors: Blank CE, Cui H, Moore LR, Walls RL
- Issue date: 2016
- BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications.
- Authors: Whetzel PL, Noy NF, Shah NH, Alexander PR, Nyulas C, Tudorache T, Musen MA
- Issue date: 2011 Jul
- Relations as patterns: bridging the gap between OBO and OWL.
- Authors: Hoehndorf R, Oellrich A, Dumontier M, Kelso J, Rebholz-Schuhmann D, Herre H
- Issue date: 2010 Aug 31
- The Ontology of Biological and Clinical Statistics (OBCS) for standardized and reproducible statistical analysis.
- Authors: Zheng J, Harris MR, Masci AM, Lin Y, Hero A, Smith B, He Y
- Issue date: 2016 Sep 14