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» Gene set analysis for longitudinal gene expression data
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BMCBI
2007
134views more  BMCBI 2007»
13 years 7 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
2004
139views more  BMCBI 2004»
13 years 7 months ago
Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels an
Background: The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge r...
Jeffrey P. Townsend
BMCBI
2006
200views more  BMCBI 2006»
13 years 7 months ago
Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data
Background: Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, clas...
Ian B. Jeffery, Desmond G. Higgins, Aedín C...
WABI
2005
Springer
14 years 29 days ago
Time-Window Analysis of Developmental Gene Expression Data with Multiple Genetic Backgrounds
d Abstract] Tamir Tuller , Efrat Oron , Erez Makavy , Daniel A. Chamovitz † , and Benny Chor ‡ Tel-Aviv University, Tel-Aviv 69978, Israel. Abstract. We study gene expression d...
Tamir Tuller, Efrat Oron, Erez Makavy, Daniel A. C...
BMCBI
2006
164views more  BMCBI 2006»
13 years 7 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta