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» Data-adaptive test statistics for microarray data
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BMCBI
2010
96views more  BMCBI 2010»
13 years 7 months ago
A statistical framework for differential network analysis from microarray data
Background: It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of gene...
Ryan Gill, Somnath Datta, Susmita Datta
BMCBI
2005
148views more  BMCBI 2005»
13 years 7 months ago
Nonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experiments
Background: Numerous nonparametric approaches have been proposed in literature to detect differential gene expression in the setting of two user-defined groups. However, there is ...
Xin Gao, Peter X. K. Song
BMCBI
2004
100views more  BMCBI 2004»
13 years 7 months ago
Handling multiple testing while interpreting microarrays with the Gene Ontology Database
Background: The development of software tools that analyze microarray data in the context of genetic knowledgebases is being pursued by multiple research groups using different me...
Michael V. Osier, Hongyu Zhao, Kei-Hoi Cheung
BMCBI
2007
159views more  BMCBI 2007»
13 years 7 months ago
Detecting differential expression in microarray data: comparison of optimal procedures
Background: Many procedures for finding differentially expressed genes in microarray data are based on classical or modified t-statistics. Due to multiple testing considerations, ...
Elena Perelman, Alexander Ploner, Stefano Calza, Y...
ISNN
2005
Springer
14 years 26 days ago
Non-parametric Statistical Tests for Informative Gene Selection
This paper presents two non-parametric statistical test methods, called Kolmogorov-Smirnov (KS) and U statistic test methods, respectively, for informative gene selection of a tumo...
Jinwen Ma, Fuhai Li, Jianfeng Liu