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BMCBI
2004
181views more  BMCBI 2004»
13 years 5 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
BMCBI
2010
116views more  BMCBI 2010»
13 years 5 months ago
FiGS: a filter-based gene selection workbench for microarray data
Background: The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene sel...
Taeho Hwang, Choong-Hyun Sun, Taegyun Yun, Gwan-Su...
ISMB
2000
13 years 6 months ago
Analysis of Gene Expression Microarrays for Phenotype Classification
Several microarray technologies that monitor the level of expression of a large number of genes have recently emerged. Given DNA-microarray data for a set of cells characterized b...
Andrea Califano, Gustavo Stolovitzky, Yuhai Tu
BMCBI
2007
182views more  BMCBI 2007»
13 years 5 months ago
Additive risk survival model with microarray data
Background: Microarray techniques survey gene expressions on a global scale. Extensive biomedical studies have been designed to discover subsets of genes that are associated with ...
Shuangge Ma, Jian Huang
ISNN
2005
Springer
13 years 11 months ago
An Information Criterion for Informative Gene Selection
It is important in bioinformatics research and applications to select or discover informative genes of a tumor from microarray data. However, most of the existing methods are based...
Fei Ge, Jinwen Ma