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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2006
153views more  BMCBI 2006»
14 years 10 months ago
Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive
Background: Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in ...
Hiro Takahashi, Takeshi Nemoto, Teruhiko Yoshida, ...
APIN
2010
108views more  APIN 2010»
14 years 10 months ago
A low variance error boosting algorithm
Abstract. This paper introduces a robust variant of AdaBoost, cwAdaBoost, that uses weight perturbation to reduce variance error, and is particularly effective when dealing with da...
Ching-Wei Wang, Andrew Hunter
BMCBI
2007
133views more  BMCBI 2007»
14 years 9 months ago
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
BMCBI
2006
155views more  BMCBI 2006»
14 years 10 months ago
Analysis of promoter regions of co-expressed genes identified by microarray analysis
Background: The use of global gene expression profiling to identify sets of genes with similar expression patterns is rapidly becoming a widespread approach for understanding biol...
Srinivas Veerla, Mattias Höglund
HCI
2007
14 years 11 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...