Mammalian Genomes Ease Location of Human DNA Functional Segments but Not Their Description
Newberg Lee A and
Lawrence Charles E
Additional contact information
Newberg Lee A: New York State Department of Health Wadsworth Center & Rensselaer Polytechnic Institute Department of Computer Science
Lawrence Charles E: Brown University Division of Applied Mathematics
Statistical Applications in Genetics and Molecular Biology, 2004, vol. 3, issue 1, 14
Abstract:
Under the assumption that a significant motivation for sequencing the genomes of mammals is the resulting ability to help us locate and characterize functional DNA segments shared with humans, we have developed a statistical analysis to quantify the expected advantage. Examining uncertainty in terms of the width of a confidence interval, we show that uncertainty in the rate of nucleotide mutation can be shrunk by a factor of nearly four when nine mammals; human, chimpanzee, baboon, cat, dog, cow, pig, rat, mouse; are used instead of just two; human and mouse. Contrastingly, we show confidence interval shrinkage by a factor of only 1.5 for measurements of the distribution of nucleotides at an aligned sequence site. These additional genomes should greatly help in identifying conserved DNA sites, but would be much less effective at precisely describing the expected pattern of nucleotides at those sites.
Keywords: Comparative genomics; Sequence Conservation; Sequence pattern identification (search for similar items in EconPapers)
Date: 2004
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://doi.org/10.2202/1544-6115.1065 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bpj:sagmbi:v:3:y:2004:i:1:n:23
Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/sagmb/html
DOI: 10.2202/1544-6115.1065
Access Statistics for this article
Statistical Applications in Genetics and Molecular Biology is currently edited by Michael P. H. Stumpf
More articles in Statistical Applications in Genetics and Molecular Biology from De Gruyter
Bibliographic data for series maintained by Peter Golla ().