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» Combined Gene Selection Methods for Microarray Data Analysis
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HCI
2007
15 years 1 months ago
FPF-SB : A Scalable Algorithm for Microarray Gene Expression Data Clustering
Efficient and effective analysis of large datasets from microarray gene expression data is one of the keys to time-critical personalized medicine. The issue we address here is the ...
Filippo Geraci, Mauro Leoncini, Manuela Montangero...
BMCBI
2008
167views more  BMCBI 2008»
14 years 11 months ago
Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments
Background: Most microarray experiments are carried out with the purpose of identifying genes whose expression varies in relation with specific conditions or in response to enviro...
Stefano Parodi, Vito Pistoia, Marco Muselli
BMCBI
2006
203views more  BMCBI 2006»
14 years 11 months ago
Genome-wide prediction of transcriptional regulatory elements of human promoters using gene expression and promoter analysis dat
Background: A complete understanding of the regulatory mechanisms of gene expression is the next important issue of genomics. Many bioinformaticians have developed methods and alg...
Seon-Young Kim, YongSung Kim
BMCBI
2006
130views more  BMCBI 2006»
14 years 11 months ago
CARMA: A platform for analyzing microarray datasets that incorporate replicate measures
Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust ex...
Kevin A. Greer, Matthew R. McReynolds, Heddwen L. ...
BIODATAMINING
2008
135views more  BIODATAMINING 2008»
14 years 11 months ago
Fast Gene Ontology based clustering for microarray experiments
Background: Analysis of a microarray experiment often results in a list of hundreds of diseaseassociated genes. In order to suggest common biological processes and functions for t...
Kristian Ovaska, Marko Laakso, Sampsa Hautaniemi