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» Gene set analysis for longitudinal gene expression data
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GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
14 years 1 months ago
A multi-objective approach to discover biclusters in microarray data
The main motivation for using a multi–objective evolutionary algorithm for finding biclusters in gene expression data is motivated by the fact that when looking for biclusters ...
Federico Divina, Jesús S. Aguilar-Ruiz
BMCBI
2006
119views more  BMCBI 2006»
13 years 7 months ago
Utilization of two sample t-test statistics from redundant probe sets to evaluate different probe set algorithms in GeneChip stu
Background: The choice of probe set algorithms for expression summary in a GeneChip study has a great impact on subsequent gene expression data analysis. Spiked-in cRNAs with know...
Zihua Hu, Gail R. Willsky
BMCBI
2005
121views more  BMCBI 2005»
13 years 7 months ago
Evaluation of gene importance in microarray data based upon probability of selection
Background: Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many import...
Li M. Fu, Casey S. Fu-Liu
BMCBI
2004
75views more  BMCBI 2004»
13 years 7 months ago
Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes
Background: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very f...
Hongying Jiang, Youping Deng, Huann-Sheng Chen, Li...
RECOMB
2008
Springer
14 years 7 months ago
Detecting Disease-Specific Dysregulated Pathways Via Analysis of Clinical Expression Profiles
We present a method for identifying connected gene subnetworks significantly enriched for genes that are dysregulated in specimens of a disease. These subnetworks provide a signat...
Igor Ulitsky, Richard M. Karp, Ron Shamir