Linked Life Data

11339905

Source:http://linkedlifedata.com/resource/pubmed/id/11339905

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2001-5-7
pubmed:abstractText
We consider the problem of inferring fold changes in gene expression from cDNA microarray data. Standard procedures focus on the ratio of measured fluorescent intensities at each spot on the microarray, but to do so is to ignore the fact that the variation of such ratios is not constant. Estimates of gene expression changes are derived within a simple hierarchical model that accounts for measurement error and fluctuations in absolute gene expression levels. Significant gene expression changes are identified by deriving the posterior odds of change within a similar model. The methods are tested via simulation and are applied to a panel of Escherichia coli microarrays.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1066-5277
pubmed:author
pubmed:issnType
Print
pubmed:volume
8
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
37-52
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
On differential variability of expression ratios: improving statistical inference about gene expression changes from microarray data.
pubmed:affiliation
Department of Statistics, University of Wisconsin, Madison, WI 53792, USA. newton@stat.wisc.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Validation Studies