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BMCBI
2007
159views more  BMCBI 2007»
13 years 9 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...
CSB
2005
IEEE
143views Bioinformatics» more  CSB 2005»
14 years 2 months ago
Multivariate gene selection: Does it help
When building predictors of disease state based on gene expression data, gene selection is performed in order to achieve a good performance and to identify a relevant subset of ge...
Carmen Lai, Marcel J. T. Reinders
BMCBI
2010
136views more  BMCBI 2010»
13 years 9 months ago
The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays
Background: Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, producti...
Yevhen Vainshtein, Mayka Sanchez, Alvis Brazma, Ma...
BMCBI
2004
100views more  BMCBI 2004»
13 years 8 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
2006
86views more  BMCBI 2006»
13 years 8 months ago
The impact of sample imbalance on identifying differentially expressed genes
Background: Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the p...
Kun Yang, Jianzhong Li, Hong Gao