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» Spot shape modelling and data transformations for microarray...
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BMCBI
2004
139views more  BMCBI 2004»
13 years 5 months ago
Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels an
Background: The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge r...
Jeffrey P. Townsend
BIOINFORMATICS
2005
72views more  BIOINFORMATICS 2005»
13 years 5 months ago
Use of within-array replicate spots for assessing differential expression in microarray experiments
Motivation. Spotted arrays are often printed with probes in duplicate or triplicate, but current methods for assessing differential expression are not able to make full use of the...
Gordon K. Smyth, Joëlle Michaud, Hamish S. Sc...
BMCBI
2005
114views more  BMCBI 2005»
13 years 5 months ago
Quality determination and the repair of poor quality spots in array experiments
Background: A common feature of microarray experiments is the occurence of missing gene expression data. These missing values occur for a variety of reasons, in particular, becaus...
Brian D. M. Tom, Walter R. Gilks, Elizabeth T. Bro...
BMCBI
2007
135views more  BMCBI 2007»
13 years 5 months ago
Measuring similarities between gene expression profiles through new data transformations
Background: Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. Finding an appropriate (dis)similarity measure is crit...
Kyungpil Kim, Shibo Zhang, Keni Jiang, Li Cai, In-...
BMCBI
2007
149views more  BMCBI 2007»
13 years 5 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...