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CBMS
2005
IEEE
14 years 2 months ago
An Ontology-Driven Clustering Method for Supporting Gene Expression Analysis
The Gene Ontology (GO) is an important knowledge resource for biologists and bioinformaticians. This paper explores the integration of similarity information derived from GO into ...
Haiying Wang, Francisco Azuaje, Olivier Bodenreide...
ISMB
2000
13 years 10 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
2004
115views more  BMCBI 2004»
13 years 8 months ago
Quantifying the relationship between co-expression, co-regulation and gene function
Background: It is thought that genes with similar patterns of mRNA expression and genes with similar functions are likely to be regulated via the same mechanisms. It has been diff...
Dominic J. Allocco, Isaac S. Kohane, Atul J. Butte
BMCBI
2008
83views more  BMCBI 2008»
13 years 9 months ago
Prioritization of gene regulatory interactions from large-scale modules in yeast
Background: The identification of groups of co-regulated genes and their transcription factors, called transcriptional modules, has been a focus of many studies about biological s...
Ho-Joon Lee, Thomas Manke, Ricardo Bringas, Martin...
BMCBI
2010
158views more  BMCBI 2010»
13 years 9 months ago
Validation of differential gene expression algorithms: Application comparing fold-change estimation to hypothesis testing
Background: Sustained research on the problem of determining which genes are differentially expressed on the basis of microarray data has yielded a plethora of statistical algorit...
Corey M. Yanofsky, David R. Bickel