Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2005-1-20
pubmed:abstractText
Comparative genome sequence analysis is powerful, but sequencing genomes is expensive. It is desirable to be able to predict how many genomes are needed for comparative genomics, and at what evolutionary distances. Here I describe a simple mathematical model for the common problem of identifying conserved sequences. The model leads to some useful rules of thumb. For a given evolutionary distance, the number of comparative genomes needed for a constant level of statistical stringency in identifying conserved regions scales inversely with the size of the conserved feature to be detected. At short evolutionary distances, the number of comparative genomes required also scales inversely with distance. These scaling behaviors provide some intuition for future comparative genome sequencing needs, such as the proposed use of "phylogenetic shadowing" methods using closely related comparative genomes, and the feasibility of high-resolution detection of small conserved features.
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-10676967, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-10973062, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-11435399, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-11801179, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12032251, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12082130, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12372296, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12433575, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12433583, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12466850, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12537575, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12610304, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12727901, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12748633, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12775844, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12917688, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-12946282, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-14624258, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-14638322, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-14668220, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-14736341, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-15059994, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-15153998, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-15215377, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-15292512, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-3934395, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-9449677, http://linkedlifedata.com/resource/pubmed/commentcorrection/15660152-9689093
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
1545-7885
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
3
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
e10
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
A model of the statistical power of comparative genome sequence analysis.
pubmed:affiliation
Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine Saint Louis, Missouri United States of America. eddy@genetics.wustl.edu
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't