An evaluation of hybrid methods for matching biomedical terminologies: mapping the gene ontology to the UMLS

Abstract

Integration of disparate biomedical terminologies is becoming increasingly important as links between biological science and clinical medicine grow. Mapping concepts in the Gene Ontology (GO) to the UMLS may help further this integration and allow for more efficient information exchange among researchers. Using a gold standard of GO term--UMLS concept mappings provided by the NCI, we examined the performance of various published and combined mapping techniques, in order to maximize precision and recall. We found that for the previously published techniques precision varied between (0.61-0.95), and recall varied from (0.65-0.90), whereas for the hybrid techniques, precision varied between (0.66-0.97), and recall from (0.59-0.93). Our study reveals the benefits of using mapping techniques that incorporate domain knowledge, and provides a basis for future approaches to mapping between distinct biomedical vocabularies.

Figure 1

Graphs representing the overall results between the two sets of methods, published and hybrid. Inflections in the graph representing hybrid methods may not exactly match the results in Table 2 due to merging of redundant data points. The hybrid graph represents data points in the incremental methods, as well as the combined results of the “voting” methods.