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» Analysis of variance components in gene expression data
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BMCBI
2011
14 years 1 months ago
Cell Subset Prediction for Blood Genomic Studies
Background: Genome-wide transcriptional profiling of patient blood samples offers a powerful tool to investigate underlying disease mechanisms and personalized treatment decisions...
Christopher R. Bolen, Mohamed Uduman, Steven H. Kl...
BMCBI
2007
152views more  BMCBI 2007»
14 years 10 months ago
Difference-based clustering of short time-course microarray data with replicates
Background: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain know...
Jihoon Kim, Ju Han Kim
BMCBI
2005
104views more  BMCBI 2005»
14 years 9 months ago
A statistical approach for array CGH data analysis
Background: Microarray-CGH experiments are used to detect and map chromosomal imbalances, by hybridizing targets of genomic DNA from a test and a reference sample to sequences imm...
Franck Picard, Stéphane Robin, Marc Laviell...
BMCBI
2007
109views more  BMCBI 2007»
14 years 10 months ago
Discarding duplicate ditags in LongSAGE analysis may introduce significant error
Background: During gene expression analysis by Serial Analysis of Gene Expression (SAGE), duplicate ditags are routinely removed from the data analysis, because they are suspected...
Jeppe Emmersen, Anna M. Heidenblut, Annabeth Laurs...
ICASSP
2009
IEEE
15 years 4 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...