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» Stratification bias in low signal microarray studies
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87
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BMCBI
2007
157views more  BMCBI 2007»
14 years 11 months ago
Improving gene set analysis of microarray data by SAM-GS
Background: Gene-set analysis evaluates the expression of biological pathways, or a priori defined gene sets, rather than that of individual genes, in association with a binary ph...
Irina Dinu, John D. Potter, Thomas Mueller, Qi Liu...
BMCBI
2010
130views more  BMCBI 2010»
14 years 11 months ago
The behaviour of random forest permutation-based variable importance measures under predictor correlation
Background: Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observ...
Kristin K. Nicodemus, James D. Malley, Carolin Str...
99
Voted
BMCBI
2010
147views more  BMCBI 2010»
14 years 11 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
BMCBI
2008
127views more  BMCBI 2008»
14 years 11 months ago
Gene and pathway identification with Lp penalized Bayesian logistic regression
Background: Identifying genes and pathways associated with diseases such as cancer has been a subject of considerable research in recent years in the area of bioinformatics and co...
Zhenqiu Liu, Ronald B. Gartenhaus, Ming Tan, Feng ...
128
Voted
BMCBI
2011
14 years 6 months ago
Comparing genotyping algorithms for Illumina's Infinium whole-genome SNP BeadChips
Background: Illumina’s Infinium SNP BeadChips are extensively used in both small and large-scale genetic studies. A fundamental step in any analysis is the processing of raw all...
Matthew E. Ritchie, Ruijie Liu, Benilton Carvalho,...