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» Clustering Genes Using Heterogeneous Data Sources
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PR
2008
88views more  PR 2008»
13 years 11 months ago
Modified global k
Clustering in gene expression data sets is a challenging problem. Different algorithms for clustering of genes have been proposed. However due to the large number of genes only a ...
Adil M. Bagirov
BMCBI
2006
171views more  BMCBI 2006»
13 years 11 months ago
The effect of oligonucleotide microarray data pre-processing on the analysis of patient-cohort studies
Background: Intensity values measured by Affymetrix microarrays have to be both normalized, to be able to compare different microarrays by removing non-biological variation, and s...
Roel G. W. Verhaak, Frank J. T. Staal, Peter J. M....
RECOMB
2009
Springer
14 years 6 months ago
Reconstructing Histories of Complex Gene Clusters on a Phylogeny
Abstract. Clusters of genes that have evolved by repeated segmental duplication present difficult challenges throughout genomic analysis, from sequence assembly to functional analy...
Tomás Vinar, Brona Brejová, Giltae S...
CCGRID
2006
IEEE
14 years 5 months ago
Using Multiple Grid Resources for Bioinformatics Applications in GADU
During the past decade, the scientific community has witnessed the rapid accumulation of gene sequence data and data related to physiology and biochemistry of organisms. Bioinform...
Dinanath Sulakhe, Alex Rodriguez, Michael Wilde, I...
BMCBI
2006
155views more  BMCBI 2006»
13 years 11 months ago
Analysis of promoter regions of co-expressed genes identified by microarray analysis
Background: The use of global gene expression profiling to identify sets of genes with similar expression patterns is rapidly becoming a widespread approach for understanding biol...
Srinivas Veerla, Mattias Höglund