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JMLR
2010
105views more  JMLR 2010»
12 years 11 months ago
Evaluation of Signaling Cascades Based on the Weights from Microarray and ChIP-seq Data
In this study, we combined the ChIP-seq and the transcriptome data and integrated these data into signaling cascades. Integration was realized through a framework based on data- a...
Zerrin Isik, Volkan Atalay, Rengül Çet...
BMCBI
2011
12 years 8 months ago
Evaluating methods for ranking differentially expressed genes applied to MicroArray Quality Control data
Background: Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and r...
Koji Kadota, Kentaro Shimizu
BMCBI
2002
188views more  BMCBI 2002»
13 years 4 months ago
The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data
Background: The biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic an...
David M. Mutch, Alvin Berger, Robert Mansourian, A...
BMCBI
2008
135views more  BMCBI 2008»
13 years 5 months ago
Knowledge-guided multi-scale independent component analysis for biomarker identification
Background: Many statistical methods have been proposed to identify disease biomarkers from gene expression profiles. However, from gene expression profile data alone, statistical...
Li Chen, Jianhua Xuan, Chen Wang, Ie-Ming Shih, Yu...
IMSCCS
2006
IEEE
13 years 11 months ago
Estimation Of Cross-Hybridization Signals Using Support Vector Regression
Microarray technology is a powerful biotechnology tool which allows researchers to simultaneously evaluate the expression of thousands of genes, if not the entire expressed genome...
Yijun Sun, Li Liu, Mick Popp, William G. Farmerie