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» Additive risk survival model with microarray data
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BMCBI
2010
124views more  BMCBI 2010»
14 years 12 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 12 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 12 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 12 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 12 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