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» Combined Gene Selection Methods for Microarray Data Analysis
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BMCBI
2005
113views more  BMCBI 2005»
15 years 2 months ago
Pathway level analysis of gene expression using singular value decomposition
Background: A promising direction in the analysis of gene expression focuses on the changes in expression of specific predefined sets of genes that are known in advance to be rela...
John K. Tomfohr, Jun Lu, Thomas B. Kepler
BIBM
2008
IEEE
217views Bioinformatics» more  BIBM 2008»
15 years 9 months ago
Combining Hierarchical Inference in Ontologies with Heterogeneous Data Sources Improves Gene Function Prediction
The study of gene function is critical in various genomic and proteomic fields. Due to the availability of tremendous amounts of different types of protein data, integrating thes...
Xiaoyu Jiang, Naoki Nariai, Martin Steffen, Simon ...
TCBB
2008
107views more  TCBB 2008»
15 years 2 months ago
Coclustering of Human Cancer Microarrays Using Minimum Sum-Squared Residue Coclustering
It is a consensus in microarray analysis that identifying potential local patterns, characterized by coherent groups of genes and conditions, may shed light on the discovery of pre...
Hyuk Cho, Inderjit S. Dhillon
133
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BMCBI
2010
124views more  BMCBI 2010»
15 years 3 months ago
A factor model to analyze heterogeneity in gene expression
Background: Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene d...
Yuna Blum, Guillaume Le Mignon, Sandrine Lagarrigu...
BMCBI
2010
161views more  BMCBI 2010»
15 years 3 months ago
GATExplorer: Genomic and Transcriptomic Explorer; mapping expression probes to gene loci, transcripts, exons and ncRNAs
Background: Genome-wide expression studies have developed exponentially in recent years as a result of extensive use of microarray technology. However, expression signals are typi...
Alberto Risueño, Celia Fontanillo, Marcel E...