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» Gene Expression Data Management: A Case Study
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ICANN
2009
Springer
13 years 6 months ago
Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data
Different algorithms have been proposed in the literature to cluster gene expression data, however there is no single algorithm that can be considered the best one independently on...
André C. A. Nascimento, Ricardo Bastos Cava...
BMCBI
2007
112views more  BMCBI 2007»
13 years 8 months ago
Integrated olfactory receptor and microarray gene expression databases
Background: Gene expression patterns of olfactory receptors (ORs) are an important component of the signal encoding mechanism in the olfactory system since they determine the inte...
Nian Liu, Chiquito J. Crasto, Minghong Ma
BMCBI
2005
97views more  BMCBI 2005»
13 years 8 months ago
Phylogenetic reconstruction of ancestral character states for gene expression and mRNA splicing data
Background: As genomes evolve after speciation, gene content, coding sequence, gene expression, and splicing all diverge with time from ancestors with close relatives. A minimum e...
Roald Rossnes, Ingvar Eidhammer, David A. Liberles
CSB
2004
IEEE
164views Bioinformatics» more  CSB 2004»
14 years 8 days ago
Biclustering in Gene Expression Data by Tendency
The advent of DNA microarray technologies has revolutionized the experimental study of gene expression. Clustering is the most popular approach of analyzing gene expression data a...
Jinze Liu, Jiong Yang, Wei Wang 0010
BMCBI
2006
200views more  BMCBI 2006»
13 years 8 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...