| Literature DB >> 31158512 |
Ian Harrow1, Rama Balakrishnan2, Ernesto Jimenez-Ruiz3, Simon Jupp4, Jane Lomax5, Jane Reed6, Martin Romacker7, Christian Senger8, Andrea Splendiani9, Jabe Wilson10, Peter Woollard11.
Abstract
In this review, we provide a summary of recent progress in ontology mapping (OM) at a crucial time when biomedical research is under a deluge of an increasing amount and variety of data. This is particularly important for realising the full potential of semantically enabled or enriched applications and for meaningful insights, such as drug discovery, using machine-learning technologies. We discuss challenges and solutions for better ontology mappings, as well as how to select ontologies before their application. In addition, we describe tools and algorithms for ontology mapping, including evaluation of tool capability and quality of mappings. Finally, we outline the requirements for an ontology mapping service (OMS) and the progress being made towards implementation of such sustainable services.Mesh:
Year: 2019 PMID: 31158512 DOI: 10.1016/j.drudis.2019.05.020
Source DB: PubMed Journal: Drug Discov Today ISSN: 1359-6446 Impact factor: 7.851