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» Improving gene set analysis of microarray data by SAM-GS
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BIBE
2003
IEEE
128views Bioinformatics» more  BIBE 2003»
14 years 25 days ago
A Repulsive Clustering Algorithm for Gene Expression Data
: - Facing the development of microarray technology, clustering is currently a leading technique to gene expression data analysis. In this paper, we propose a novel algorithm calle...
Chyun-Shin Cheng, Shiuan-Sz Wang
BIBM
2009
IEEE
192views Bioinformatics» more  BIBM 2009»
14 years 2 months ago
A Multi-task Feature Selection Filter for Microarray Classification
A major challenge in microarray classification and biomarker discovery is dealing with small-sample high-dimensional data where the number of genes used as features is typically o...
Liang Lan, Slobodan Vucetic
BMCBI
2006
153views more  BMCBI 2006»
13 years 7 months ago
Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments
Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
IEEEMM
2007
146views more  IEEEMM 2007»
13 years 7 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
IJBRA
2010
89views more  IJBRA 2010»
13 years 6 months ago
Strategies for enhanced annotation of a microarray probe set
—We aim to determine the biological relevance of genes identified through microarray-mediated transcriptional profiling of Xenopus sensory organs and brain tissue. Genetic data...
TuShun R. Powers, Selene M. Virk, Elba E. Serrano