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» Improving gene set analysis of microarray data by SAM-GS
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BMCBI
2011
13 years 2 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso
BMCBI
2007
120views more  BMCBI 2007»
13 years 7 months ago
Transcript-based redefinition of grouped oligonucleotide probe sets using AceView: High-resolution annotation for microarrays
Background: Extracting biological information from high-density Affymetrix arrays is a multi-step process that begins with the accurate annotation of microarray probes. Shortfalls...
Jun Lu, Joseph C. Lee, Marc L. Salit, Margaret C. ...
BMCBI
2004
180views more  BMCBI 2004»
13 years 7 months ago
Noise filtering and nonparametric analysis of microarray data underscores discriminating markers of oral, prostate, lung, ovaria
Background: A major goal of cancer research is to identify discrete biomarkers that specifically characterize a given malignancy. These markers are useful in diagnosis, may identi...
Virginie M. Aris, Michael J. Cody, Jeff Cheng, Jam...
BMCBI
2004
75views more  BMCBI 2004»
13 years 7 months ago
Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes
Background: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very f...
Hongying Jiang, Youping Deng, Huann-Sheng Chen, Li...
FUIN
2002
123views more  FUIN 2002»
13 years 7 months ago
Learning Rough Set Classifiers from Gene Expressions and Clinical Data
Biological research is currently undergoing a revolution. With the advent of microarray technology the behavior of thousands of genes can be measured simultaneously. This capabilit...
Herman Midelfart, Henryk Jan Komorowski, Kristin N...