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» Analyzing time series gene expression data
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BMCBI
2010
125views more  BMCBI 2010»
13 years 7 months ago
Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types
Background: Much of the public access cancer microarray data is asymmetric, belonging to datasets containing no samples from normal tissue. Asymmetric data cannot be used in stand...
Noor B. Dawany, Aydin Tozeren
BMCBI
2008
94views more  BMCBI 2008»
13 years 7 months ago
A comprehensive re-analysis of the Golden Spike data: Towards a benchmark for differential expression methods
Background: The Golden Spike data set has been used to validate a number of methods for summarizing Affymetrix data sets, sometimes with seemingly contradictory results. Much less...
Richard D. Pearson
BMCBI
2005
163views more  BMCBI 2005»
13 years 7 months ago
Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data
Background: The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustm...
Nitin Jain, HyungJun Cho, Michael O'Connell, Jae K...
BMCBI
2004
97views more  BMCBI 2004»
13 years 7 months ago
Calibration and assessment of channel-specific biases in microarray data with extended dynamical range
Background: Non-linearities in observed log-ratios of gene expressions, also known as intensity dependent log-ratios, can often be accounted for by global biases in the two channe...
Henrik Bengtsson, Göran Jönsson, Johan V...
CGF
2010
146views more  CGF 2010»
13 years 7 months ago
Pathline: A Tool For Comparative Functional Genomics
Biologists pioneering the new field of comparative functional genomics attempt to infer the mechanisms of gene regulation by looking for similarities and differences of gene activ...
Miriah D. Meyer, Bang Wong, Mark P. Styczynski, Ta...