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BMCBI
2007
134views more  BMCBI 2007»
15 years 6 months ago
A framework for significance analysis of gene expression data using dimension reduction methods
Background: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, ide...
Lars Halvor Gidskehaug, Endre Anderssen, Arnar Fla...
BMCBI
2005
153views more  BMCBI 2005»
15 years 6 months ago
A comparative review of estimates of the proportion unchanged genes and the false discovery rate
Background: In the analysis of microarray data one generally produces a vector of p-values that for each gene give the likelihood of obtaining equally strong evidence of change by...
Per Broberg
BMCBI
2006
82views more  BMCBI 2006»
15 years 6 months ago
Prediction of a key role of motifs binding E2F and NR2F in down-regulation of numerous genes during the development of the mouse
Background: We previously demonstrated that gene expression profiles during neuronal differentiation in vitro and hippocampal development in vivo were very similar, due to a conse...
Michal Dabrowski, Stein Aerts, Bozena Kaminska
HICSS
2006
IEEE
138views Biometrics» more  HICSS 2006»
16 years 15 days ago
Explaining ICT Infrastructure and E-Commerce Uses and Benefits in Industrial Clusters: Evidence from a Biotech Cluster
The literature on industrial clusters has not focused heavily on the role of the ICT infrastructure, nor on the potential implications of electronic commerce . In this paper, we e...
Charles Steinfield, Ada Scupola
BIOINFORMATICS
2004
119views more  BIOINFORMATICS 2004»
15 years 6 months ago
Analysis of variance components in gene expression data
Motivation: A microarray experiment is a multi-step process, and each step is a potential source of variation. There are two major sources of variation: biological variation and t...
James J. Chen, Robert R. Delongchamp, Chen-An Tsai...