IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v90y2004i1p213-228.html
   My bibliography  Save this article

Ontology concepts and tools for statistical genomics

Author

Listed:
  • Carey, V.J.Vincent J.

Abstract

In computer science, an ontology is any formally structured vocabulary covering a conceptual domain. Gene Ontology (GO) is a structured collection of terms defining biological processes, cellular components, or molecular functions for the purpose of characterizing gene products and functions. The structure of GO is a directed acyclic graph (DAG) with typed edges. We describe a simple formalism for working with ontologies for statistical purposes, and define object-ontology complexes, which encode the usage of the vocabulary to label objects under analysis. Recently developed concepts of information content and semantic similarity are evaluated and used to explore the association between LocusLink loci and GO. We investigate relations between GO DAG structure, association evidence codes and term information content, illustrate computation of semantic similarities of genes within and between clusters discovered in a microarray, and describe a more general ontology and its use in inference on genetic network structure.

Suggested Citation

  • Carey, V.J.Vincent J., 2004. "Ontology concepts and tools for statistical genomics," Journal of Multivariate Analysis, Elsevier, vol. 90(1), pages 213-228, July.
  • Handle: RePEc:eee:jmvana:v:90:y:2004:i:1:p:213-228
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(04)00022-3
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jmvana:v:90:y:2004:i:1:p:213-228. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.