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» Stratification bias in low signal microarray studies
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BMCBI
2007
157views more  BMCBI 2007»
14 years 9 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 9 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...
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BMCBI
2010
147views more  BMCBI 2010»
14 years 9 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 9 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 ...
BMCBI
2011
14 years 4 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,...