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» Class discovery in gene expression data
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BMCBI
2007
125views more  BMCBI 2007»
13 years 7 months ago
Bayesian meta-analysis models for microarray data: a comparative study
Background: With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis...
Erin M. Conlon, Joon J. Song, Anna Liu
BMCBI
2010
170views more  BMCBI 2010»
13 years 7 months ago
Integrative analysis of gene expression and copy number alterations using canonical correlation analysis
Background: With the rapid development of new genetic measurement methods, several types of genetic alterations can be quantified in a high-throughput manner. While the initial fo...
Charlotte Soneson, Henrik Lilljebjörn, Thoas ...
ALMOB
2007
111views more  ALMOB 2007»
13 years 7 months ago
Transcriptional regulatory network discovery via multiple method integration: application to e. coli K12
Motivation: Transcriptional regulatory network (TRN) discovery from one method (e.g. microarray analysis, gene ontology, phylogenic similarity) does not seem feasible due to lack ...
Jingjun Sun, Kagan Tuncay, Alaa Abi Haidar, Lisa E...
ICML
2005
IEEE
14 years 8 months ago
Active learning for sampling in time-series experiments with application to gene expression analysis
Many time-series experiments seek to estimate some signal as a continuous function of time. In this paper, we address the sampling problem for such experiments: determining which ...
Rohit Singh, Nathan Palmer, David K. Gifford, Bonn...
BMCBI
2006
116views more  BMCBI 2006»
13 years 7 months ago
ROKU: a novel method for identification of tissue-specific genes
Background: One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We wo...
Koji Kadota, Jiazhen Ye, Yuji Nakai, Tohru Terada,...