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» Semantic Mining and Analysis of Gene Expression Data
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BMCBI
2006
131views more  BMCBI 2006»
13 years 9 months ago
The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison
Background: Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, t...
Allan A. Sioson, Shrinivasrao P. Mane, Pinghua Li,...
BMCBI
2006
155views more  BMCBI 2006»
13 years 9 months ago
A powerful method for detecting differentially expressed genes from GeneChip arrays that does not require replicates
Background: Studies of differential expression that use Affymetrix GeneChip arrays are often carried out with a limited number of replicates. Reasons for this include financial co...
Anne-Mette K. Hein, Sylvia Richardson
BMCBI
2006
164views more  BMCBI 2006»
13 years 9 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
DSS
2007
127views more  DSS 2007»
13 years 8 months ago
Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
BMCBI
2010
183views more  BMCBI 2010»
13 years 6 months ago
The complexity of gene expression dynamics revealed by permutation entropy
Background: High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation En...
Xiaoliang Sun, Yong Zou, Victoria J. Nikiforova, J...