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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
BMCBI
2005
101views more  BMCBI 2005»
13 years 4 months ago
MASQOT: a method for cDNA microarray spot quality control
Background: cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying ...
Max Bylesjö, Daniel Eriksson, Andreas Sjö...
BMCBI
2005
144views more  BMCBI 2005»
13 years 4 months ago
Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in
Background: Comparison of data produced on different microarray platforms often shows surprising discordance. It is not clear whether this discrepancy is caused by noisy data or b...
Scott L. Carter, Aron C. Eklund, Brigham H. Mecham...
BMCBI
2004
132views more  BMCBI 2004»
13 years 4 months ago
Two-stage normalization using background intensities in cDNA microarray data
Background: In the microarray experiment, many undesirable systematic variations are commonly observed. Normalization is the process of removing such variation that affects the me...
Dankyu Yoon, Sung-Gon Yi, Ju-Han Kim, Taesung Park
BMCBI
2004
161views more  BMCBI 2004»
13 years 4 months ago
Three-parameter lognormal distribution ubiquitously found in cDNA microarray data and its application to parametric data treatme
Background: To cancel experimental variations, microarray data must be normalized prior to analysis. Where an appropriate model for statistical data distribution is available, a p...
Tomokazu Konishi