A visual analytics approach for understanding biclustering results from microarray data.
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Visual analytics in cheminformatics: user-supervised descriptor selection for QSAR methodsAnalysis of biomedical data with multilevel glyphsRecursive expectation-maximization clustering: a method for identifying buffering mechanisms composed of phenomic modules.Furby: fuzzy force-directed bicluster visualizationForce feature spaces for visualization and classification.
P2860
A visual analytics approach for understanding biclustering results from microarray data.
description
2008 nî lūn-bûn
@nan
2008 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
A visual analytics approach for understanding biclustering results from microarray data.
@ast
A visual analytics approach for understanding biclustering results from microarray data.
@en
type
label
A visual analytics approach for understanding biclustering results from microarray data.
@ast
A visual analytics approach for understanding biclustering results from microarray data.
@en
prefLabel
A visual analytics approach for understanding biclustering results from microarray data.
@ast
A visual analytics approach for understanding biclustering results from microarray data.
@en
P2093
P2860
P50
P356
P1433
P1476
A visual analytics approach for understanding biclustering results from microarray data
@en
P2093
Luis Quintales
Roberto Therón
Rodrigo Santamaría
P2860
P2888
P356
10.1186/1471-2105-9-247
P577
2008-05-27T00:00:00Z
P5875
P6179
1038242636