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» Semantic Mining and Analysis of Gene Expression Data
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BIBE
2007
IEEE
155views Bioinformatics» more  BIBE 2007»
14 years 3 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
2007
138views more  BMCBI 2007»
13 years 9 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
BMCBI
2006
201views more  BMCBI 2006»
13 years 9 months ago
Gene selection algorithms for microarray data based on least squares support vector machine
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
BMCBI
2002
147views more  BMCBI 2002»
13 years 8 months ago
Expression profiling of human renal carcinomas with functional taxonomic analysis
Background: Molecular characterization has contributed to the understanding of the inception, progression, treatment and prognosis of cancer. Nucleic acid array-based technologies...
Michael A. Gieseg, Theresa Cody, Michael Z. Man, S...
BMCBI
2008
159views more  BMCBI 2008»
13 years 9 months ago
Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
Hongya Zhao, Kwok-Leung Chan, Lee-Ming Cheng, Hong...