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» Smoothing Gene Expression Using Biological Networks
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BMCBI
2006
147views more  BMCBI 2006»
13 years 9 months ago
Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data
Background: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find...
Alex Lewin, Ian C. Grieve
BMCBI
2005
167views more  BMCBI 2005»
13 years 8 months ago
Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes
Background: The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer...
Patrick Warnat, Roland Eils, Benedikt Brors
BMCBI
2007
182views more  BMCBI 2007»
13 years 9 months ago
Identifying regulatory targets of cell cycle transcription factors using gene expression and ChIP-chip data
Background: ChIP-chip data, which indicate binding of transcription factors (TFs) to DNA regions in vivo, are widely used to reconstruct transcriptional regulatory networks. Howev...
Wei-Sheng Wu, Wen-Hsiung Li, Bor-Sen Chen
GFKL
2005
Springer
141views Data Mining» more  GFKL 2005»
14 years 2 months ago
On External Indices for Mixtures: Validating Mixtures of Genes
Mixture models represent results of gene expression cluster analysis in a more natural way than ’hard’ partitions. This is also true for the representation of gene labels, such...
Ivan G. Costa, Alexander Schliep
KDD
2009
ACM
249views Data Mining» more  KDD 2009»
14 years 9 months ago
Drosophila gene expression pattern annotation using sparse features and term-term interactions
The Drosophila gene expression pattern images document the spatial and temporal dynamics of gene expression and they are valuable tools for explicating the gene functions, interac...
Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, ...