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CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
13 years 7 months ago
Minimum Entropy Clustering and Applications to Gene Expression Analysis
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Haifeng Li, Keshu Zhang, Tao Jiang
SDM
2004
SIAM
187views Data Mining» more  SDM 2004»
13 years 5 months ago
Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data
Microarray experiments have been extensively used for simultaneously measuring DNA expression levels of thousands of genes in genome research. A key step in the analysis of gene e...
Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvri...
APBC
2004
164views Bioinformatics» more  APBC 2004»
13 years 5 months ago
Cluster Ensemble and Its Applications in Gene Expression Analysis
Huge amount of gene expression data have been generated as a result of the human genomic project. Clustering has been used extensively in mining these gene expression data to find...
Xiaohua Hu, Illhoi Yoo
BIBE
2007
IEEE
155views Bioinformatics» more  BIBE 2007»
13 years 10 months ago
Partial Mixture Model for Tight Clustering in Exploratory Gene Expression Analysis
Abstract—In this paper we demonstrate the inherent robustness of minimum distance estimator that makes it a potentially powerful tool for parameter estimation in gene expression ...
Yinyin Yuan, Chang-Tsun Li
BMCBI
2010
183views more  BMCBI 2010»
13 years 1 months ago
The complexity of gene expression dynamics revealed by permutation entropy
Background: High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation En...
Xiaoliang Sun, Yong Zou, Victoria J. Nikiforova, J...