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» The ParTriCluster Algorithm for Gene Expression Analysis
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BMCBI
2010
216views more  BMCBI 2010»
14 years 7 months ago
Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies
Background: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors f...
Bo Chen, Minhua Chen, John William Paisley, Aimee ...
73
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BMCBI
2005
110views more  BMCBI 2005»
15 years 12 days ago
Considerations when using the significance analysis of microarrays (SAM) algorithm
Background: Users of microarray technology typically strive to use universally acceptable data analysis strategies to determine significant expression changes in their experiments...
Ola Larsson, Claes Wahlestedt, James A. Timmons
103
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BMCBI
2005
154views more  BMCBI 2005»
15 years 12 days ago
GObar: A Gene Ontology based analysis and visualization tool for gene sets
Background: Microarray experiments, as well as other genomic analyses, often result in large gene sets containing up to several hundred genes. The biological significance of such ...
Jason S. M. Lee, Gurpreet Katari, Ravi Sachidanand...
121
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BMCBI
2006
170views more  BMCBI 2006»
15 years 17 days ago
Biclustering of gene expression data by non-smooth non-negative matrix factorization
Background: The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of gene...
Pedro Carmona-Saez, Roberto D. Pascual-Marqui, Fra...
85
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KDD
2004
ACM
314views Data Mining» more  KDD 2004»
16 years 28 days ago
Assessment of discretization techniques for relevant pattern discovery from gene expression data
In the domain of gene expression data analysis, various researchers have recently emphasized the promising application of pattern discovery techniques like association rule mining...
Ruggero G. Pensa, Claire Leschi, Jéré...