Linked Life Data

11867083

Source:http://linkedlifedata.com/resource/pubmed/id/11867083

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2002-2-27
pubmed:abstractText
A popular commercially available oligonucleotide microarray technology employs sets of 25 base pair oligonucleotide probes for measurement of gene expression levels. A mathematical algorithm is required to compute an estimate of gene expression from the multiple probes. Previously proposed methods for summarizing gene expression data have either been substantially ad hoc or have relied on model assumptions that may be easily violated. Here we present a new algorithm for calculating gene expression from probe sets. Our approach is functionally related to leave-one-out cross-validation, a non-parametric statistical technique that is often applied in limited data situations. We illustrate this approach using data from our study seeking a molecular fingerprint of STAT3 regulated genes for early detection of human cancer.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
0025-5564
pubmed:author
pubmed:issnType
Print
pubmed:volume
176
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
53-8
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
A simple method to improve probe set estimates from oligonucleotide arrays.
pubmed:affiliation
H. Lee Moffitt Cancer Center & Research Institute, University of South Florida, 12902 Magnolia Drive, MRC-CANCONT Tampa, FL 33612-9497, USA. lazarien@iarc.fr
pubmed:publicationType
Journal Article