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BMCBI
2006
92views more  BMCBI 2006»
14 years 9 months ago
Predicting survival outcomes using subsets of significant genes in prognostic marker studies with microarrays
Background: Genetic markers hold great promise for refining our ability to establish precise prognostic prediction for diseases. The development of comprehensive gene expression m...
Shigeyuki Matsui
BMCBI
2010
181views more  BMCBI 2010»
14 years 9 months ago
Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one ...
Amit Zeisel, Amnon Amir, Wolfgang J. Köstler,...
BMCBI
2007
173views more  BMCBI 2007»
14 years 9 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
CIBCB
2006
IEEE
15 years 1 months ago
Efficient Probe Selection in Microarray Design
Abstract-- The DNA microarray technology, originally developed to measure the level of gene expression, had become one of the most widely used tools in genomic study. Microarrays h...
Leszek Gasieniec, Cindy Y. Li, Paul Sant, Prudence...
BMCBI
2004
158views more  BMCBI 2004»
14 years 9 months ago
A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...