| pubmed-article:16970825 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:16970825 | lifeskim:mentions | umls-concept:C0040223 | lld:lifeskim |
| pubmed-article:16970825 | lifeskim:mentions | umls-concept:C0017262 | lld:lifeskim |
| pubmed-article:16970825 | lifeskim:mentions | umls-concept:C1880022 | lld:lifeskim |
| pubmed-article:16970825 | lifeskim:mentions | umls-concept:C0449445 | lld:lifeskim |
| pubmed-article:16970825 | lifeskim:mentions | umls-concept:C1710548 | lld:lifeskim |
| pubmed-article:16970825 | pubmed:dateCreated | 2006-10-5 | lld:pubmed |
| pubmed-article:16970825 | pubmed:abstractText | A semiparametric approach was used to identify groups of cDNAs and genes with distinct expression profiles across time and overcome the limitations of clustering to identify groups. The semiparametric approach allows the generalization of mixtures of distributions while making no specific parametric assumptions about the distribution of the hidden heterogeneity of the cDNAs. The semiparametric approach was applied to study gene expression in the brains of Apis mellifera ligustica honey bees raised in two colonies (A. m. mellifera and ligustica) with consistent patterns across five maturation ages. | lld:pubmed |
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| pubmed-article:16970825 | pubmed:language | eng | lld:pubmed |
| pubmed-article:16970825 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:16970825 | pubmed:citationSubset | IM | lld:pubmed |
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| pubmed-article:16970825 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:16970825 | pubmed:issn | 1471-2164 | lld:pubmed |
| pubmed-article:16970825 | pubmed:author | pubmed-author:WhitfieldChar... | lld:pubmed |
| pubmed-article:16970825 | pubmed:author | pubmed-author:RobinsonGene... | lld:pubmed |
| pubmed-article:16970825 | pubmed:author | pubmed-author:Rodriguez-Zas... | lld:pubmed |
| pubmed-article:16970825 | pubmed:author | pubmed-author:SoutheyBruce... | lld:pubmed |
| pubmed-article:16970825 | pubmed:issnType | Electronic | lld:pubmed |
| pubmed-article:16970825 | pubmed:volume | 7 | lld:pubmed |
| pubmed-article:16970825 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:16970825 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:16970825 | pubmed:pagination | 233 | lld:pubmed |
| pubmed-article:16970825 | pubmed:dateRevised | 2011-8-1 | lld:pubmed |
| pubmed-article:16970825 | pubmed:meshHeading | pubmed-meshheading:16970825... | lld:pubmed |
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| pubmed-article:16970825 | pubmed:meshHeading | pubmed-meshheading:16970825... | lld:pubmed |
| pubmed-article:16970825 | pubmed:meshHeading | pubmed-meshheading:16970825... | lld:pubmed |
| pubmed-article:16970825 | pubmed:meshHeading | pubmed-meshheading:16970825... | lld:pubmed |
| pubmed-article:16970825 | pubmed:meshHeading | pubmed-meshheading:16970825... | lld:pubmed |
| pubmed-article:16970825 | pubmed:year | 2006 | lld:pubmed |
| pubmed-article:16970825 | pubmed:articleTitle | Semiparametric approach to characterize unique gene expression trajectories across time. | lld:pubmed |
| pubmed-article:16970825 | pubmed:affiliation | Department of Animal Sciences, University of Illinois at Urbana-Champaign, IL 61801, USA. rodrgzzs@uiuc.edu | lld:pubmed |
| pubmed-article:16970825 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:16970825 | pubmed:publicationType | Research Support, N.I.H., Extramural | lld:pubmed |
| pubmed-article:16970825 | pubmed:publicationType | Validation Studies | lld:pubmed |
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