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» Clustering cancer gene expression data: a comparative study
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BMCBI
2005
145views more  BMCBI 2005»
15 years 6 months ago
CAGER: classification analysis of gene expression regulation using multiple information sources
Background: Many classification approaches have been applied to analyzing transcriptional regulation of gene expressions. These methods build models that can explain a gene's...
Jianhua Ruan, Weixiong Zhang
BMCBI
2004
128views more  BMCBI 2004»
15 years 6 months ago
Comparing transformation methods for DNA microarray data
Background: When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed ...
Helene H. Thygesen, Aeilko H. Zwinderman
CIBCB
2006
IEEE
16 years 7 days ago
A Model-Free Greedy Gene Selection for Microarray Sample Class Prediction
— Microarray data analysis is notoriously challenging as it involves a huge number of genes compared to only a limited number of samples. Gene selection, to detect the most signi...
Yi Shi, Zhipeng Cai, Lizhe Xu, Wei Ren, Randy Goeb...
BMCBI
2008
97views more  BMCBI 2008»
15 years 6 months ago
MCM-test: a fuzzy-set-theory-based approach to differential analysis of gene pathways
Background: Gene pathway can be defined as a group of genes that interact with each other to perform some biological processes. Along with the efforts to identify the individual g...
Lily R. Liang, Vinay Mandal, Yi Lu, Deepak Kumar
HIPC
2009
Springer
15 years 4 months ago
Comparing the performance of clusters, Hadoop, and Active Disks on microarray correlation computations
Abstract--Microarray-based comparative genomic hybridization (aCGH) offers an increasingly fine-grained method for detecting copy number variations in DNA. These copy number variat...
Jeffrey A. Delmerico, Nathanial A. Byrnes, Andrew ...