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» Weighted analysis of general microarray experiments
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BMCBI
2010
214views more  BMCBI 2010»
13 years 7 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
WCE
2007
13 years 8 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
BMCBI
2008
104views more  BMCBI 2008»
13 years 7 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...
JDWM
2007
122views more  JDWM 2007»
13 years 7 months ago
A Hyper-Heuristic for Descriptive Rule Induction
Rule induction from examples is a machine learning technique that finds rules of the form condition → class, where condition and class are logic expressions of the form variable...
Tho Hoan Pham, Tu Bao Ho
BMCBI
2011
13 years 2 months ago
The impact of quantitative optimization of hybridization conditions on gene expression analysis
Background: With the growing availability of entire genome sequences, an increasing number of scientists can exploit oligonucleotide microarrays for genome-scale expression studie...
Peter Sykacek, David P. Kreil, Lisa A. Meadows, Ri...