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» Classification of microarray data using gene networks
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BMCBI
2006
124views more  BMCBI 2006»
15 years 2 months ago
Network-based de-noising improves prediction from microarray data
Background: Prediction of human cell response to anti-cancer drugs (compounds) from microarray data is a challenging problem, due to the noise properties of microarrays as well as...
Tsuyoshi Kato, Yukio Murata, Koh Miura, Kiyoshi As...
CBMS
2006
IEEE
15 years 4 months ago
Incorporating Gene Ontology in Clustering Gene Expression Data
In this paper we consider a general framework for clustering expression data that permits integration of various biological data sources through combination of corresponding dissi...
Rafal Kustra, Adam Zagdanski
122
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BMCBI
2010
151views more  BMCBI 2010»
15 years 2 months ago
BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets
Background: The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design ...
Mark J. Alston, John Seers, Jay C. D. Hinton, Sach...
SAC
2006
ACM
15 years 8 months ago
Two-phase clustering strategy for gene expression data sets
In the context of genome research, the method of gene expression analysis has been used for several years. Related microarray experiments are conducted all over the world, and con...
Dirk Habich, Thomas Wächter, Wolfgang Lehner,...
BMCBI
2007
129views more  BMCBI 2007»
15 years 2 months ago
HoughFeature, a novel method for assessing drug effects in three-color cDNA microarray experiments
Background: Three-color microarray experiments can be performed to assess drug effects on the genomic scale. The methodology may be useful in shortening the cycle, reducing the co...
Hongya Zhao, Hong Yan