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BMCBI
2004
113views more  BMCBI 2004»
13 years 8 months ago
Leveraging two-way probe-level block design for identifying differential gene expression with high-density oligonucleotide array
Background: To identify differentially expressed genes across experimental conditions in oligonucleotide microarray experiments, existing statistical methods commonly use a summar...
Leah Barrera, Chris Benner, Yong-Chuan Tao, Elizab...
BMCBI
2008
179views more  BMCBI 2008»
13 years 8 months ago
Improving the power for detecting overlapping genes from multiple DNA microarray-derived gene lists
Background: In DNA microarray gene expression profiling studies, a fundamental task is to extract statistically significant genes that meet certain research hypothesis. Currently,...
Xutao Deng, Jun Xu, Charles Wang
BMCBI
2008
98views more  BMCBI 2008»
13 years 8 months ago
Empirical Bayes models for multiple probe type microarrays at the probe level
Background: When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are...
Magnus Åstrand, Petter Mostad, Mats Rudemo
BMCBI
2007
127views more  BMCBI 2007»
13 years 8 months ago
A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments
Background: With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across...
Hyungwon Choi, Ronglai Shen, Arul M. Chinnaiyan, D...
BMCBI
2007
126views more  BMCBI 2007»
13 years 8 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...