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1: Bioinformatics. 2003 Jul 1;19(10):1275-83.
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Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation.

Lord PW, Stevens RD, Brass A, Goble CA.

Department of Computer Science, University of Manchester, Oxford Road, Manchester, M13 9PL, UK. p.lord@russet.org.uk

MOTIVATION: Many bioinformatics data resources not only hold data in the form of sequences, but also as annotation. In the majority of cases, annotation is written as scientific natural language: this is suitable for humans, but not particularly useful for machine processing. Ontologies offer a mechanism by which knowledge can be represented in a form capable of such processing. In this paper we investigate the use of ontological annotation to measure the similarities in knowledge content or 'semantic similarity' between entries in a data resource. These allow a bioinformatician to perform a similarity measure over annotation in an analogous manner to those performed over sequences. A measure of semantic similarity for the knowledge component of bioinformatics resources should afford a biologist a new tool in their repertoire of analyses. RESULTS: We present the results from experiments that investigate the validity of using semantic similarity by comparison with sequence similarity. We show a simple extension that enables a semantic search of the knowledge held within sequence databases. AVAILABILITY: Software available from http://www.russet.org.uk.

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PMID: 12835272 [PubMed - indexed for MEDLINE]