Abstract
Ontologies are fundamental knowledge representations that provide not only standards for annotating and indexing biological information, but also the basis for implementing functional classification and interpretation models. This chapter discusses the application of gene ontology (GO) for predictive tasks in functional genomics. It focuses on the problem of analyzing functional patterns associated with gene products. This chapter is divided into two main parts. The first part overviews GO and its applications for the development of functional classification models. The second part presents two methods for the characterization of genomic information using GO. It discusses methods for measuring functional similarity of gene products, and a tool for supporting gene expression clustering analysis and validation.
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Acknowledgment
We thank Oliver Bodenreider for helpful advice on ontologies. This work was supported by grant BIO2001-0068 from the Ministerio de Ciencia y Tecnología. F.A. was partly supported by a visiting fellowship from the US National Library of Medicine.
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Azuaje, F., Al-Shahrour, F., Dopazo, J. (2006). Ontology-Driven Approaches to Analyzing Data in Functional Genomics. In: Larson, R.S. (eds) Bioinformatics and Drug Discovery. Methods in Molecular Biology, vol 316. Humana Press. https://doi.org/10.1385/1-59259-964-8:67
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DOI: https://doi.org/10.1385/1-59259-964-8:67
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