Source:http://linkedlifedata.com/resource/pubmed/id/18718939
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rdf:type | |
lifeskim:mentions | |
pubmed:issue |
21
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pubmed:dateCreated |
2008-10-21
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pubmed:abstractText |
Nested effects models (NEMs) are a class of probabilistic models introduced to analyze the effects of gene perturbation screens visible in high-dimensional phenotypes like microarrays or cell morphology. NEMs reverse engineer upstream/downstream relations of cellular signaling cascades. NEMs take as input a set of candidate pathway genes and phenotypic profiles of perturbing these genes. NEMs return a pathway structure explaining the observed perturbation effects. Here, we describe the package nem, an open-source software to efficiently infer NEMs from data. Our software implements several search algorithms for model fitting and is applicable to a wide range of different data types and representations. The methods we present summarize the current state-of-the-art in NEMs. AVAILABILITY: Our software is written in the R language and freely avail-able via the Bioconductor project at http://www.bioconductor.org.
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pubmed:grant | |
pubmed:commentsCorrections |
http://linkedlifedata.com/resource/pubmed/commentcorrection/18718939-12431377,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18718939-15461798,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18718939-16159925,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18718939-17646311,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18718939-17903286,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18718939-17937790,
http://linkedlifedata.com/resource/pubmed/commentcorrection/18718939-18285370
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pubmed:language |
eng
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pubmed:journal | |
pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:month |
Nov
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pubmed:issn |
1367-4811
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pubmed:author | |
pubmed:issnType |
Electronic
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pubmed:day |
1
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pubmed:volume |
24
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
2549-50
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pubmed:dateRevised |
2010-9-21
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pubmed:meshHeading |
pubmed-meshheading:18718939-Algorithms,
pubmed-meshheading:18718939-Gene Expression,
pubmed-meshheading:18718939-Gene Expression Profiling,
pubmed-meshheading:18718939-Models, Statistical,
pubmed-meshheading:18718939-Oligonucleotide Array Sequence Analysis,
pubmed-meshheading:18718939-Software,
pubmed-meshheading:18718939-User-Computer Interface
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pubmed:year |
2008
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pubmed:articleTitle |
Analyzing gene perturbation screens with nested effects models in R and bioconductor.
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pubmed:affiliation |
German Cancer Research Center, INF 580, 69120 Heidelberg, Germany.
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pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, Non-P.H.S.,
Research Support, Non-U.S. Gov't,
Research Support, N.I.H., Extramural
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