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rdf:type |
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lifeskim:mentions |
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pubmed:dateCreated |
2011-6-20
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pubmed:abstractText |
Normalization of gene expression data has been studied for many years and various strategies have been formulated to deal with various types of data. Most normalization algorithms rely on the assumption that the number of up-regulated genes and the number of down-regulated genes are roughly the same. However, the well-known Golden Spike experiment presents a unique situation in which differentially regulated genes are biased toward one direction, thereby challenging the conclusions of previous bench mark studies.
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pubmed:commentsCorrections |
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-12202253,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-12538238,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-12925520,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-15693945,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-15948292,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-16473874,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-16527929,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-16953902,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-17177995,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-17204140,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-17384014,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-17445265,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-17640361,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-17713554,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-18366762,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-19055840,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-19357096,
http://linkedlifedata.com/resource/pubmed/commentcorrection/21631915-9126387
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:issn |
1471-2105
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pubmed:author |
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pubmed:issnType |
Electronic
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pubmed:volume |
12
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
222
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pubmed:dateRevised |
2011-10-12
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pubmed:meshHeading |
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pubmed:year |
2011
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pubmed:articleTitle |
Kernel density weighted loess normalization improves the performance of detection within asymmetrical data.
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pubmed:affiliation |
Institute of Statistics, National Tsing Hua University, Hsin-Chu City, 300, Taiwan. wphsieh@stat.nthu.edu.tw
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pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
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