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» Spotting effect in microarray experiments
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BMCBI
2004
106views more  BMCBI 2004»
13 years 4 months ago
Spotting effect in microarray experiments
Background: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...
Tristan Mary-Huard, Jean-Jacques Daudin, Sté...
CBMS
2007
IEEE
13 years 11 months ago
An Unsupervised and Fully-Automated Image Analysis Method for cDNA Microarrays
Microarray gene expression image analysis is a labor-intensive task and requires human intervention since microarray images are contaminated with noise and artifacts while spots a...
Eleni Zacharia, Dimitrios E. Maroulis
JEI
2007
176views more  JEI 2007»
13 years 4 months ago
Adaptive techniques for microarray image analysis with related quality assessment
We propose novel techniques for microarray image analysis. In particular, we describe an overall pipeline able to solve the most common problems of microarray image analysis. We pr...
Sebastiano Battiato, Gianpiero di Blasi, Giovanni ...
BMCBI
2005
148views more  BMCBI 2005»
13 years 4 months ago
Nonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experiments
Background: Numerous nonparametric approaches have been proposed in literature to detect differential gene expression in the setting of two user-defined groups. However, there is ...
Xin Gao, Peter X. K. Song
BMCBI
2005
126views more  BMCBI 2005»
13 years 4 months ago
An algorithm for automatic evaluation of the spot quality in two-color DNA microarray experiments
Background: Although DNA microarray technologies are very powerful for the simultaneous quantitative characterization of thousands of genes, the quality of the obtained experiment...
Eugene Novikov, Emmanuel Barillot