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» Analysis of Microarray Titration Experiments
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CSDA
2008
128views more  CSDA 2008»
13 years 8 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
WCE
2007
13 years 9 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
2007
130views more  BMCBI 2007»
13 years 8 months ago
A robust measure of correlation between two genes on a microarray
Background: The underlying goal of microarray experiments is to identify gene expression patterns across different experimental conditions. Genes that are contained in a particula...
Johanna S. Hardin, Aya Mitani, Leanne Hicks, Brian...
BMCBI
2004
127views more  BMCBI 2004»
13 years 8 months ago
Optimized LOWESS normalization parameter selection for DNA microarray data
Background: Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normaliza...
John A. Berger, Sampsa Hautaniemi, Anna-Kaarina J&...
BMCBI
2006
147views more  BMCBI 2006»
13 years 8 months ago
Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data
Background: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find...
Alex Lewin, Ian C. Grieve