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BMCBI
2008
110views more  BMCBI 2008»
13 years 7 months ago
Testing for treatment effects on gene ontology
In studies that use DNA arrays to assess changes in gene expression, it is preferable to measure the significance of treatment effects on a group of genes from a pathway or functi...
Taewon Lee, Varsha G. Desai, Cruz Velasco, Robert ...
BMCBI
2006
99views more  BMCBI 2006»
13 years 7 months ago
A proposed metric for assessing the measurement quality of individual microarrays
Background: High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that...
Kyoungmi Kim, Grier P. Page, T. Mark Beasley, Step...
CSDA
2006
90views more  CSDA 2006»
13 years 7 months ago
Estimation in covariate-adjusted regression
Abstract: The method of covariate adjusted regression was recently proposed for situations where both predictors and response in a regression model are not directly observed, but a...
Damla Sentürk, Danh V. Nguyen
BMCBI
2007
148views more  BMCBI 2007»
13 years 7 months ago
Computation of significance scores of unweighted Gene Set Enrichment Analyses
Background: Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for in...
Andreas Keller, Christina Backes, Hans-Peter Lenho...
BMCBI
2007
147views more  BMCBI 2007»
13 years 7 months ago
Bias in random forest variable importance measures: Illustrations, sources and a solution
Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and relate...
Carolin Strobl, Anne-Laure Boulesteix, Achim Zeile...