IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v64y2002i4p681-693.html
   My bibliography  Save this article

Bayesian phylogenetic inference from animal mitochondrial genome arrangements

Author

Listed:
  • Bret Larget
  • Donald L. Simon
  • Joseph B. Kadane

Abstract

Summary. The determination of evolutionary relationships is a fundamental problem in evolutionary biology. Genome arrangement data are potentially more informative than deoxyribonucleic acid sequence data for inferring evolutionary relationships between distantly related taxa. We describe a Bayesian framework for phylogenetic inference from mitochondrial genome arrangement data using Markov chain Monte Carlo methods. We apply the method to assess evolutionary relationships between eight animal phyla.

Suggested Citation

  • Bret Larget & Donald L. Simon & Joseph B. Kadane, 2002. "Bayesian phylogenetic inference from animal mitochondrial genome arrangements," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 681-693, October.
    • Handle: RePEc:bla:jorssb:v:64:y:2002:i:4:p:681-693
    DOI: 10.1111/1467-9868.00356
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1467-9868.00356
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1467-9868.00356?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:bla:jorssb:v:64:y:2002:i:4:p:681-693. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.