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» Clustering of Gene Expression Data: Performance and Similari...
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BMCBI
2008
115views more  BMCBI 2008»
14 years 9 months ago
Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient
Background: Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson corre...
Jianchao Yao, Chunqi Chang, Mari L. Salmi, Yeung S...
BMCBI
2008
102views more  BMCBI 2008»
14 years 9 months ago
Response projected clustering for direct association with physiological and clinical response data
Background: Microarray gene expression data are often analyzed together with corresponding physiological response and clinical metadata of biological subjects, e.g. patients'...
Sung-Gon Yi, Taesung Park, Jae K. Lee
BMCBI
2004
162views more  BMCBI 2004»
14 years 9 months ago
Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant m
Background: Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression p...
Rajalakshmi Gurunathan, Bernard Van Emden, Sethura...
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NIPS
2003
14 years 11 months ago
ICA-based Clustering of Genes from Microarray Expression Data
We propose an unsupervised methodology using independent component analysis (ICA) to cluster genes from DNA microarray data. Based on an ICA mixture model of genomic expression pa...
Su-In Lee, Serafim Batzoglou
BMCBI
2008
133views more  BMCBI 2008»
14 years 9 months ago
A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data
Background: Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible f...
Luca Corradi, Marco Fato, Ivan Porro, Silvia Scagl...