Fisher Hannah M, Hoehndorf Robert, Bazelato Bruno S, Dadras Soheil S, King Lloyd E, Gkoutos Georgios V, Sundberg John P, Schofield Paul N
Dept. of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK.
Computational Bioscience Research Center, King Abdullah University of Science and Technology, 23955-6900, Thuwal, Kingdom of Saudi Arabia.
J Biomed Semantics. 2016 Jun 13;7:38. doi: 10.1186/s13326-016-0085-x.
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.
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.
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.
为皮肤病制定标准分类法和术语集的举措屡见不鲜，有些专门针对该领域，有些则是更大术语集（如国际疾病分类第十版，ICD - 10）的一部分。近来，形式化结构的术语集，即本体，在生物医学研究的许多领域得到广泛发展。这些本体主要旨在为知识领域提供全面的实用术语集，但由于术语之间关系中所包含的知识，它们还可在计算方面用于多种目的。
我们开发了一种皮肤病本体，由领域专家手动构建。DermO包含3000多个术语，是现有最全面的正式皮肤病学疾病术语集。疾病实体被归类为20个上位术语，这些上位术语依据解剖位置、遗传性、受影响的细胞或组织类型或病因等多种特征进行分类，这与皮肤病学的专业实践和分类法一致。它有OBO平面文件和OWL 2格式，在语义上与描述疾病和表型的其他本体及术语集集成。我们展示了DermO在生物医学文献文本挖掘以及创建描述皮肤病表型关系网络方面的应用。
DermO是一个广泛覆盖皮肤病领域的本体，我们在此展示了其在文本挖掘以及皮肤病表型关系研究中的效用。我们设想，未来它可应用于电子健康记录的创建与挖掘、临床培训和基础研究，因为它支持自动推理，还能将皮肤病信息与其他领域的信息更广泛地整合。
