Linked Life Data

1731067

Source:http://linkedlifedata.com/resource/pubmed/id/1731067

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
1992-2-19
pubmed:abstractText
An Expectation Maximization algorithm for identification of DNA binding sites is presented. The approach predicts the location of binding regions while allowing variable length spacers within the sites. In addition to predicting the most likely spacer length for a set of DNA fragments, the method identifies individual sites that differ in spacer size. No alignment of DNA sequences is necessary. The method is illustrated by application to 231 Escherichia coli DNA fragments known to contain promoters with variable spacings between their consensus regions. Maximum-likelihood tests of the differences between the spacing classes indicate that the consensus regions of the spacing classes are not distinct. Further tests suggest that several positions within the spacing region may contribute to promoter specificity.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
0022-2836
pubmed:author
pubmed:issnType
Print
pubmed:day
5
pubmed:volume
223
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
159-70
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
1992
pubmed:articleTitle
Expectation maximization algorithm for identifying protein-binding sites with variable lengths from unaligned DNA fragments.
pubmed:affiliation
Institute for Behavior Genetics, University of Colorado Boulder 80309-0447.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, P.H.S.