Datamining with Ontologies.
The use of ontologies has increased rapidly over the past decade and they now provide a key component of most major databases in biology and biomedicine. Consequently, datamining over these databases benefits from considering the specific structure and content of ontologies, and several methods have been developed to use ontologies in datamining applications. Here, we discuss the principles of ontology structure, and datamining methods that rely on ontologies. The impact of these methods in the biological and biomedical sciences has been profound and is likely to increase as more datasets are becoming available using common, shared ontologies.
Computational Bioscience Research Center, King Abdullah University of Science and Technology, 4700 King Abdullah University of Science and Technology, Thuwal, 23955-6900, Kingdom of Saudi Arabia. robert.hoehndorf@kaust.edu.sa.
Robert
R
Hoehndorf
Department of Computer Science, Aberystwyth University, Llandinam Building, Aberystwyth, SY23 3DB, UK.
Georgios V
GV
Gkoutos
Department of Physiology, Development & Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK.
Paul N
PN
Schofield
D000465:Algorithms; D064229:Biological Ontologies; D019295:Computational Biology; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D000075403:Semantic Web
Automated reasoning; Data integration; Enrichment; Graph algorithms; Ontology; Semantic Web; Semantic similarity; Web Ontology Language (OWL)