Abstract
Biological data about genes, proteins, and biologically relevant molecules, that are stored in databases, may be associated to biological information (knowledge) such as experiments, properties and functions, response to drugs, etc. Such knowledge is formally structured in ontologies that provide the best formalization to organize and store knowledge. Consequently, it is possible to introduce novel analytical methodologies that are based on the use of ontologies. An example is represented by semantic similarities, i.e., the calculation of the similarity of two or more proteins starting from their annotations. For instance, semantic measures have been used for the prediction of protein complexes. Otherwise, functional enrichment analysis methods ensure the discovery of the functions of the input list of genes by using annotations. This chapter describes the main biomedical ontologies presented in the literature and their bioinformatic applications. Then, the principal semantic similarity measures are presented. Finally, the treatment of functional enrichment analysis concludes the chapter.
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