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» Clustering cancer gene expression data: a comparative study
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BMCBI
2007
149views more  BMCBI 2007»
15 years 6 months ago
Novel and simple transformation algorithm for combining microarray data sets
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...
RECOMB
2008
Springer
16 years 6 months ago
Reconstructing the Evolutionary History of Complex Human Gene Clusters
Abstract. Clusters of genes that evolved from single progenitors via repeated segmental duplications present significant challenges to the generation of a truly complete human geno...
Adam C. Siepel, Eric D. Green, Giltae Song, Tom&aa...
RECOMB
2010
Springer
16 years 20 days ago
Hierarchical Generative Biclustering for MicroRNA Expression Analysis
Clustering methods are a useful and common first step in gene expression studies, but the results may be hard to interpret. We bring in explicitly an indicator of which genes tie ...
José Caldas, Samuel Kaski
BMCBI
2006
114views more  BMCBI 2006»
15 years 6 months ago
A methodology for global validation of microarray experiments
Background: DNA microarrays are popular tools for measuring gene expression of biological samples. This ever increasing popularity is ensuring that a large number of microarray st...
Mathieu Miron, Owen Z. Woody, Alexandre Marcil, Ca...
BMCBI
2010
112views more  BMCBI 2010»
15 years 6 months ago
PhenoFam-gene set enrichment analysis through protein structural information
Background: With the current technological advances in high-throughput biology, the necessity to develop tools that help to analyse the massive amount of data being generated is e...
Maciej Paszkowski-Rogacz, Mikolaj Slabicki, M. Ter...