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Bioinformatics Vol. 19 Suppl. 1 2003
Pages i74-i80
© 2003 Oxford University Press

Fast identification and statistical evaluation of segmental homologies in comparative maps

Peter P. Calabrese 1, Sugata Chakravarty 2 and Todd J. Vision 3,*

1 Department of Mathematics, University of Southern California, Los Angeles, CA 90089, USA
2 Department of Operations Research
3 Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA

Received on January 6, 2003 ; accepted on February 20, 2003

Motivation: Chromosomal segments that share common ancestry, either through genomic duplication or species divergence, are said to be segmental homologs of one another. Their identification allows researchers to leverage knowledge of model organisms for use in other systems and is of value for studies of genome evolution. However, identification and statistical evaluation of segmental homologies can be a challenge when the segments are highly diverged.

Results: We describe a flexible dynamic programming algorithm for the identification of segments having multiple homologous features. We model the probability of observing putative segmental homologies by chance and incorporate our findings into the parameterization of the algorithm and the statistical evaluation of its output. Combined, these findings allow segmental homologies to be identified in comparisons within and between genomic maps in a rigorous, rapid, and automated fashion.

Availability: http://www.bio.unc.edu/faculty/vision/lab/

Contact: tjv{at}bio.unc.edu

Keywords: homology, comparative maps, synteny, genome evolution

* To whom correspondence should be addressed.


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