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BMCBI
2010
164views more  BMCBI 2010»
9 years 3 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
BMCBI
2004
181views more  BMCBI 2004»
9 years 5 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
BMCBI
2008
104views more  BMCBI 2008»
9 years 6 months ago
Missing value imputation improves clustering and interpretation of gene expression microarray data
Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...
BMCBI
2007
129views more  BMCBI 2007»
9 years 6 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
MSV
2004
9 years 7 months ago
MABAC - Matrix Based Clustering Algorithm
Clustering is a prominent method in the data mining field. It is a discovery process that groups data such that intra cluster similarity is maximized and the inter cluster similar...
Yonghui Chen, Alan P. Sprague, Kevin D. Reilly
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