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BMCBI
2008
142views more  BMCBI 2008»
14 years 9 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
BMCBI
2006
143views more  BMCBI 2006»
14 years 9 months ago
Discovering functional gene expression patterns in the metabolic network of Escherichia coli with wavelets transforms
Background: Microarray technology produces gene expression data on a genomic scale for an endless variety of organisms and conditions. However, this vast amount of information nee...
Rainer König, Gunnar Schramm, Marcus Oswald, ...
BMCBI
2006
131views more  BMCBI 2006»
14 years 9 months ago
Hybridization interactions between probesets in short oligo microarrays lead to spurious correlations
Background: Microarrays measure the binding of nucleotide sequences to a set of sequence specific probes. This information is combined with annotation specifying the relationship ...
Michal J. Okoniewski, Crispin J. Miller
BMCBI
2011
14 years 1 months ago
A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
Background: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) ...
Alfredo A. Kalaitzis, Neil D. Lawrence
RECOMB
2007
Springer
15 years 9 months ago
Comparative Analysis of Spatial Patterns of Gene Expression in Drosophila melanogaster Imaginal Discs
Determining the precise spatial extent of expression of genes across different tissues, along with knowledge of the biochemical function of the genes is critical for understanding ...
Cyrus L. Harmon, Parvez Ahammad, Ann Hammonds, Ric...