alexa Semantic similarity measures as tools for exploring the gene ontology.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Computer Science & Systems Biology

Author(s): Lord PW, Stevens RD, Brass A, Goble CA

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Abstract Many bioinformatics resources hold data in the form of sequences. Often this sequence data is associated with a large amount of annotation. In many cases this data has been hard to model, and has been represented as scientific natural language, which is not readily computationally amenable. The development of the Gene Ontology provides us with a more accessible representation of some of this data. However it is not clear how this data can best be searched, or queried. Recently we have adapted information content based measures for use with the Gene Ontology (GO). In this paper we present detailed investigation of the properties of these measures, and examine various properties of GO, which may have implications for its future design.
This article was published in Pac Symp Biocomput and referenced in Journal of Computer Science & Systems Biology

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