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BMCBI
2008
137views more  BMCBI 2008»
14 years 9 months ago
VennMaster: Area-proportional Euler diagrams for functional GO analysis of microarrays
Background: Microarray experiments generate vast amounts of data. The functional context of differentially expressed genes can be assessed by querying the Gene Ontology (GO) datab...
Hans A. Kestler, André Müller, Johann ...
BICOB
2009
Springer
14 years 7 months ago
A Biclustering Method to Discover Co-regulated Genes Using Diverse Gene Expression Datasets
We propose a two-step biclustering approach to mine co-regulation patterns of a given reference gene to discover other genes that function in a common biological process. Currently...
Doruk Bozdag, Jeffrey D. Parvin, Ümit V. &Cce...
RECOMB
2001
Springer
15 years 10 months ago
Class discovery in gene expression data
Recent studies (Alizadeh et al, [1]; Bittner et al,[5]; Golub et al, [11]) demonstrate the discovery of putative disease subtypes from gene expression data. The underlying computa...
Amir Ben-Dor, Nir Friedman, Zohar Yakhini
BMCBI
2008
94views more  BMCBI 2008»
14 years 9 months ago
A comprehensive re-analysis of the Golden Spike data: Towards a benchmark for differential expression methods
Background: The Golden Spike data set has been used to validate a number of methods for summarizing Affymetrix data sets, sometimes with seemingly contradictory results. Much less...
Richard D. Pearson
CIBCB
2006
IEEE
15 years 3 months ago
A Model-Free Greedy Gene Selection for Microarray Sample Class Prediction
— Microarray data analysis is notoriously challenging as it involves a huge number of genes compared to only a limited number of samples. Gene selection, to detect the most signi...
Yi Shi, Zhipeng Cai, Lizhe Xu, Wei Ren, Randy Goeb...