Research Article
No access
Published Online: 22 September 2008

DUPCAR: Reconstructing Contiguous Ancestral Regions with Duplications

Publication: Journal of Computational Biology
Volume 15, Issue Number 8

Abstract

Accurately reconstructing the large-scale gene order in an ancestral genome is a critical step to better understand genome evolution. In this paper, we propose a heuristic algorithm, called DUPCAR, for reconstructing ancestral genomic orders with duplications. The method starts from the order of genes in modern genomes and predicts predecessor and successor relationships in the ancestor. Then a greedy algorithm is used to reconstruct the ancestral orders by connecting genes into contiguous regions based on predicted adjacencies. Computer simulation was used to validate the algorithm. We also applied the method to reconstruct the ancestral chromosome X of placental mammals and the ancestral genomes of the ciliate Paramecium tetraurelia.

Get full access to this article

View all available purchase options and get full access to this article.

Information & Authors

Information

Published In

cover image Journal of Computational Biology
Journal of Computational Biology
Volume 15Issue Number 8October 2008
Pages: 1007 - 1027
PubMed: 18774902

History

Published in print: October 2008
Published online: 22 September 2008
Published ahead of print: 6 September 2008

Permissions

Request permissions for this article.

Topics

Authors

Affiliations

Jian Ma
Center for Biomolecular Science and Engineering, University of California, Santa Cruz, California.
Aakrosh Ratan
Center for Comparative Genomics and Bioinformatics, Penn State University, University Park, Pennsylvania.
Brian J. Raney
Center for Biomolecular Science and Engineering, University of California, Santa Cruz, California.
Bernard B. Suh
Center for Biomolecular Science and Engineering, University of California, Santa Cruz, California.
Louxin Zhang
Department of Mathematics, National University of Singapore, Singapore.
Webb Miller
Center for Comparative Genomics and Bioinformatics, Penn State University, University Park, Pennsylvania.
David Haussler
Center for Biomolecular Science and Engineering, University of California, Santa Cruz, California.

Metrics & Citations

Metrics

Citations

Export citation

Select the format you want to export the citations of this publication.

View Options

Get Access

Access content

To read the fulltext, please use one of the options below to sign in or purchase access.

Society Access

If you are a member of a society that has access to this content please log in via your society website and then return to this publication.

Restore your content access

Enter your email address to restore your content access:

Note: This functionality works only for purchases done as a guest. If you already have an account, log in to access the content to which you are entitled.

View options

PDF/EPUB

View PDF/ePub

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share on social media

Topics

Back to Top