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BMCBI
2006
165views more  BMCBI 2006»
13 years 6 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin
BMCBI
2008
179views more  BMCBI 2008»
13 years 6 months ago
Improving the power for detecting overlapping genes from multiple DNA microarray-derived gene lists
Background: In DNA microarray gene expression profiling studies, a fundamental task is to extract statistically significant genes that meet certain research hypothesis. Currently,...
Xutao Deng, Jun Xu, Charles Wang
GECCO
2004
Springer
113views Optimization» more  GECCO 2004»
14 years 2 days ago
Implications of Epigenetic Learning Via Modification of Histones on Performance of Genetic Programming
Extending the notion of inheritable genotype in genetic programming (GP) from the common model of DNA into chromatin (DNA and histones), we propose an approach of embedding in GP a...
Ivan Tanev, Kikuo Yuta
BMCBI
2007
159views more  BMCBI 2007»
13 years 6 months ago
Detecting differential expression in microarray data: comparison of optimal procedures
Background: Many procedures for finding differentially expressed genes in microarray data are based on classical or modified t-statistics. Due to multiple testing considerations, ...
Elena Perelman, Alexander Ploner, Stefano Calza, Y...
BMCBI
2007
147views more  BMCBI 2007»
13 years 6 months ago
Statistical analysis and significance testing of serial analysis of gene expression data using a Poisson mixture model
Background: Serial analysis of gene expression (SAGE) is used to obtain quantitative snapshots of the transcriptome. These profiles are count-based and are assumed to follow a Bin...
Scott D. Zuyderduyn