|
rdf:type |
|
|
lifeskim:mentions |
umls-concept:C0013570,
umls-concept:C0017262,
umls-concept:C0079941,
umls-concept:C0185117,
umls-concept:C0205245,
umls-concept:C0205314,
umls-concept:C0205426,
umls-concept:C0439792,
umls-concept:C0679622,
umls-concept:C0681842,
umls-concept:C0936012,
umls-concept:C1511726,
umls-concept:C1709061,
umls-concept:C2911684
|
|
pubmed:dateCreated |
2008-10-3
|
|
pubmed:abstractText |
Microarrays have the capacity to measure the expressions of thousands of genes in parallel over many experimental samples. The unsupervised classification technique of bicluster analysis has been employed previously to uncover gene expression correlations over subsets of samples with the aim of providing a more accurate model of the natural gene functional classes. This approach also has the potential to aid functional annotation of unclassified open reading frames (ORFs). Until now this aspect of biclustering has been under-explored. In this work we illustrate how bicluster analysis may be extended into a 'semi-supervised' ORF annotation approach referred to as BALBOA.
|
|
pubmed:commentsCorrections |
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-10618406,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-10676951,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-10929718,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-11102521,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-11120680,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-11507037,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-11752246,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-11779842,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-11836209,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-12089522,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-12429058,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-12671006,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-12801874,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-12935334,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-15631638,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-16144809,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-17217516,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18831786-9843981
|
|
pubmed:language |
eng
|
|
pubmed:journal |
|
|
pubmed:citationSubset |
IM
|
|
pubmed:status |
MEDLINE
|
|
pubmed:issn |
1471-2164
|
|
pubmed:author |
|
|
pubmed:issnType |
Electronic
|
|
pubmed:volume |
9 Suppl 2
|
|
pubmed:owner |
NLM
|
|
pubmed:authorsComplete |
Y
|
|
pubmed:pagination |
S20
|
|
pubmed:dateRevised |
2009-11-18
|
|
pubmed:meshHeading |
pubmed-meshheading:18831786-Algorithms,
pubmed-meshheading:18831786-Cluster Analysis,
pubmed-meshheading:18831786-Computational Biology,
pubmed-meshheading:18831786-Gene Expression,
pubmed-meshheading:18831786-Gene Expression Profiling,
pubmed-meshheading:18831786-Genome, Fungal,
pubmed-meshheading:18831786-Models, Statistical,
pubmed-meshheading:18831786-Oligonucleotide Array Sequence Analysis,
pubmed-meshheading:18831786-Open Reading Frames,
pubmed-meshheading:18831786-Pattern Recognition, Automated,
pubmed-meshheading:18831786-Saccharomyces cerevisiae
|
|
pubmed:year |
2008
|
|
pubmed:articleTitle |
Extending bicluster analysis to annotate unclassified ORFs and predict novel functional modules using expression data.
|
|
pubmed:affiliation |
Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland. kenneth.bryan@ucd.ie
|
|
pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't,
Validation Studies
|
