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BMCBI
2004
169views more  BMCBI 2004»
13 years 5 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
BMCBI
2010
181views more  BMCBI 2010»
13 years 5 months ago
Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one ...
Amit Zeisel, Amnon Amir, Wolfgang J. Köstler,...
BMCBI
2007
127views more  BMCBI 2007»
13 years 5 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
2004
90views more  BMCBI 2004»
13 years 5 months ago
Statistical monitoring of weak spots for improvement of normalization and ratio estimates in microarrays
Background: Several aspects of microarray data analysis are dependent on identification of genes expressed at or near the limits of detection. For example, regression-based normal...
Igor Dozmorov, Nicholas Knowlton, Yuhong Tang, Mic...
CSB
2003
IEEE
153views Bioinformatics» more  CSB 2003»
13 years 10 months ago
Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks
We propose a statistical method for estimating a gene network based on Bayesian networks from microarray gene expression data together with biological knowledge including protein-...
Seiya Imoto, Tomoyuki Higuchi, Takao Goto, Kousuke...