Investigating semantic similarity measuresacross the Gene Ontology: the relationship betweensequence and annotation

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 mech...

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Veröffentlicht in:Bioinformatics 2003-07, Vol.19 (10), p.1275-1283
Hauptverfasser: Lord, P. W., Stevens, R. D., Brass, A., Goble, C. A.
Format: Artikel
Sprache:eng ; jpn
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Zusammenfassung: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 repetoire 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 Contact: p.lord@russet.org.uk * To whom correspondence should be addressed.
ISSN:1367-4803
1460-2059
DOI:10.1093/bioinformatics/btg153