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» Classification of microarray data using gene networks
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BMCBI
2007
168views more  BMCBI 2007»
14 years 11 months ago
Bayesian model-based inference of transcription factor activity
Background: In many approaches to the inference and modeling of regulatory interactions using microarray data, the expression of the gene coding for the transcription factor is co...
Simon Rogers, Raya Khanin, Mark Girolami
BMCBI
2011
14 years 3 months ago
Evaluating methods for ranking differentially expressed genes applied to MicroArray Quality Control data
Background: Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and r...
Koji Kadota, Kentaro Shimizu
BMCBI
2005
80views more  BMCBI 2005»
14 years 11 months ago
Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm
Background: Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently ...
Kevin Dawson, Raymond L. Rodriguez, Wasyl Malyj
JCB
2000
103views more  JCB 2000»
14 years 11 months ago
Testing for Differentially-Expressed Genes by Maximum-Likelihood Analysis of Microarray Data
Although two-color uorescent DNA microarrays are now standard equipment in many molecular biology laboratories, methods for identifying differentially expressed genes in microarra...
Trey Ideker, Vesteinn Thorsson, Andrew F. Siegel, ...
CIBCB
2006
IEEE
15 years 5 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...