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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2005
137views more  BMCBI 2005»
15 years 1 months ago
A standard curve based method for relative real time PCR data processing
Background: Currently real time PCR is the most precise method by which to measure gene expression. The method generates a large amount of raw numerical data and processing may no...
Alexey Larionov, Andreas Krause, William Miller
BMCBI
2006
108views more  BMCBI 2006»
15 years 1 months ago
Probe set algorithms: is there a rational best bet?
Affymetrix microarrays have become a standard experimental platform for studies of mRNA expression profiling. Their success is due, in part, to the multiple oligonucleotide featur...
Jinwook Seo, Eric P. Hoffman
RECOMB
2004
Springer
16 years 1 months ago
Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga...
Manuel Middendorf, Anshul Kundaje, Chris Wiggins, ...
ICCSA
2005
Springer
15 years 7 months ago
A Penalized Likelihood Estimation on Transcriptional Module-Based Clustering
In this paper, we propose a new clustering procedure for high dimensional microarray data. Major difficulty in cluster analysis of microarray data is that the number of samples to ...
Ryo Yoshida, Seiya Imoto, Tomoyuki Higuchi
CSB
2004
IEEE
152views Bioinformatics» more  CSB 2004»
15 years 5 months ago
Comparative Analysis of Gene Sets in the Gene Ontology Space under the Multiple Hypothesis Testing Framework
The Gene Ontology (GO) resource can be used as a powerful tool to uncover the properties shared among, and specific to, a list of genes produced by high-throughput functional geno...
Sheng Zhong, Lu Tian, Cheng Li, Kai-Florian Storch...