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» Detecting differential expression in microarray data: compar...
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BMCBI
2007
146views more  BMCBI 2007»
13 years 4 months ago
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
BMCBI
2006
146views more  BMCBI 2006»
13 years 4 months ago
A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls
Background: Statistical comparison of peptide profiles in biomarker discovery requires fast, userfriendly software for high throughput data analysis. Important features are flexib...
Mark K. Titulaer, Ivar Siccama, Lennard J. Dekker,...
BMCBI
2008
162views more  BMCBI 2008»
13 years 4 months ago
Background correction using dinucleotide affinities improves the performance of GCRMA
Background: High-density short oligonucleotide microarrays are a primary research tool for assessing global gene expression. Background noise on microarrays comprises a significan...
Raad Z. Gharaibeh, Anthony Fodor, Cynthia Gibas
BMCBI
2006
104views more  BMCBI 2006»
13 years 4 months ago
Semi-supervised discovery of differential genes
Background: Various statistical scores have been proposed for evaluating the significance of genes that may exhibit differential expression between two or more controlled conditio...
Shigeyuki Oba, Shin Ishii
BMCBI
2008
117views more  BMCBI 2008»
13 years 4 months ago
New resampling method for evaluating stability of clusters
Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...
Irina Gana Dresen, Tanja Boes, Johannes Hüsin...