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» Microarray results: how accurate are they
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CSDA
2008
128views more  CSDA 2008»
13 years 10 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
BMCBI
2004
100views more  BMCBI 2004»
13 years 9 months ago
Handling multiple testing while interpreting microarrays with the Gene Ontology Database
Background: The development of software tools that analyze microarray data in the context of genetic knowledgebases is being pursued by multiple research groups using different me...
Michael V. Osier, Hongyu Zhao, Kei-Hoi Cheung
BMCBI
2008
95views more  BMCBI 2008»
13 years 10 months ago
Gene set analyses for interpreting microarray experiments on prokaryotic organisms
Background: Despite the widespread usage of DNA microarrays, questions remain about how best to interpret the wealth of gene-by-gene transcriptional levels that they measure. Rece...
Nathan L. Tintle, Aaron A. Best, Matthew DeJongh, ...
BMCBI
2006
156views more  BMCBI 2006»
13 years 10 months ago
Bayesian models for pooling microarray studies with multiple sources of replications
Background: Biologists often conduct multiple but different cDNA microarray studies that all target the same biological system or pathway. Within each study, replicate slides with...
Erin M. Conlon, Joon J. Song, Jun S. Liu
BMCBI
2004
208views more  BMCBI 2004»
13 years 9 months ago
Hybrid clustering for microarray image analysis combining intensity and shape features
Background: Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identif...
Jörg Rahnenführer, Daniel Bozinov