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Handbook on Ontologies pp 735–756Cite as

Application of Ontologies in Bioinformatics

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Part of the book series: International Handbooks on Information Systems ((INFOSYS))

Summary

The use of ontologies has become a mainstream activity within bioinformatics. In a largely descriptive science such as biology, the need to have a common understanding of things described is obvious. The need to be able to apply computational methods to the large quantities of data being produced also suggests a computational requirement to standardise descriptions in biology.

As a mechanism for describing the categories of entities and their characteristics, ontologies offer many of the features that can support a descriptive science. The main use of ontologies in bioinformatics has been the delivery of controlled vocabularies. In this chapter we explore this use of ontology, but also other uses, especially those that have a deeper computational aspect. We take a broad view of ontology to include many ontology-like resources and classify the uses of ontology and ontology-like artifacts. We present a series of case studies and conclude by describing the current state and future directions for bio-ontologies.

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Notes

  1. 1.

    Here we take a broad definition of bioinformatics to mean the storage, management and analysis of biological data by computational means to answer biological questions.

  2. 2.

    http://www.geneontology.org

  3. 3.

    The less common term “poset” or partially ordered set is also used.

  4. 4.

    http://www.geneontology.org/GO.current.annotations.shtml

  5. 5.

    At least judged by the number of tools available; microarray tools form the largest subsection of related tools on the GO website (http://www.geneontology.org/GO.tools.shtml).

  6. 6.

    In this section, we will talk exclusively about GO, as it is the ontology which has been statistically analysed most widely. Most of the techniques could also apply to other ontologies.

  7. 7.

    The left-hand side of the reaction.

  8. 8.

    The right-hand side of the reaction.

  9. 9.

    The enzyme classification number.

  10. 10.

    http://www.w3.org/2001/sw/HCLS

  11. 11.

    The sequence of amino acid residues in a protein determine how the protein “folds” into a three-dimensional shape. This shape determines the functionality of the protein. Biologists have determined some patterns of amino acid residue that indicate certain features of these “shapes” that are diagnostic for functionality.

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Authors and Affiliations

  1. School of Computer Science, University of Manchester, Oxford Road, M13 9PL, Manchester, UK

    Robert Stevens

  2. School of Computing Science, Newcastle University, Claremont Road, NE1 7RU, Newcastle, Upon Tyne, UK

    Phillip Lord

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  1. Inst. Informatik, Universität Koblenz-Landau, Universitaetsstr. 1, Koblenz, 56016, Germany

    Steffen Staab

  2. Inst. Angewandte Informatik und, Universität Karlsruhe, Karlsruhe, 76128, Germany

    Rudi Studer

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Stevens, R., Lord, P. (2009). Application of Ontologies in Bioinformatics. In: Staab, S., Studer, R. (eds) Handbook on Ontologies. International Handbooks on Information Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92673-3_33

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