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» Additive risk survival model with microarray data
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BMCBI
2010
124views more  BMCBI 2010»
14 years 9 months ago
A factor model to analyze heterogeneity in gene expression
Background: Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene d...
Yuna Blum, Guillaume Le Mignon, Sandrine Lagarrigu...
BMCBI
2008
120views more  BMCBI 2008»
14 years 9 months ago
A protein interaction based model for schizophrenia study
Background: Schizophrenia is a complex disease with multiple factors contributing to its pathogenesis. In addition to environmental factors, genetic factors may also increase susc...
Pei-Chun Hsu, Ueng-Cheng Yang, Kuan-Hui Shih, Chih...
BMCBI
2010
120views more  BMCBI 2010»
14 years 10 months ago
Modeling expression quantitative trait loci in data combining ethnic populations
Background: Combining data from different ethnic populations in a study can increase efficacy of methods designed to identify expression quantitative trait loci (eQTL) compared to...
Ching-Lin Hsiao, Ie-Bin Lian, Ai-Ru Hsieh, Cathy S...
BMCBI
2008
178views more  BMCBI 2008»
14 years 9 months ago
Identification of coherent patterns in gene expression data using an efficient biclustering algorithm and parallel coordinate vi
Background: The DNA microarray technology allows the measurement of expression levels of thousands of genes under tens/hundreds of different conditions. In microarray data, genes ...
Kin-On Cheng, Ngai-Fong Law, Wan-Chi Siu, Alan Wee...
BMCBI
2008
162views more  BMCBI 2008»
14 years 9 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