journal article·2022-05-21Open access

Towards an Ontology-Based Phenotypic Query Model

Christoph Beger, Franz Matthies, Ralph Schäfermeier, Toralf Kirsten, Heinrich Herre, Alexandr Uciteli

Applied Sciences· Volume 12· Issue 10

Abstract

Clinical research based on data from patient or study data management systems plays an important role in transferring basic findings into the daily practices of physicians. To support study recruitment, diagnostic processes, and risk factor evaluation, search queries for such management systems can be used. Typically, the query syntax as well as the underlying data structure vary greatly between different data management systems. This makes it difficult for domain experts (e.g., clinicians) to build and execute search queries. In this work, the Core Ontology of Phenotypes is used as a general model for phenotypic knowledge. This knowledge is required to create search queries that determine and classify individuals (e.g., patients or study participants) whose morphology, function, behaviour, or biochemical and physiological properties meet specific phenotype classes. A specific model describing a set of particular phenotype classes is called a Phenotype Specification Ontology. Such an ontology can be automatically converted to search queries on data management systems. The methods described have already been used successfully in several projects. Using ontologies to model phenotypic knowledge on patient or study data management systems is a viable approach. It allows clinicians to model from a domain perspective without knowing the actual data structure or query language.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Biomedical Text Mining and Ontologies · Semantic Web and Ontologies · Scientific Computing and Data Management

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, 04107 Leipzig, Germany

Growth Network CrescNet, Leipzig University, 04103 Leipzig, Germany

SMITH Consortium of the German Medical Informatics Initiative, 04103 Leipzig, Germany

Department Medical Data Science, Leipzig University Medical Center, 04107 Leipzig, Germany

Funding

German Federal Ministry of Education and Research · SMITH

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