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CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
13 years 10 months ago
Latent Structure Models for the Analysis of Gene Expression Data
Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
Dong Hua, Dechang Chen, Xiuzhen Cheng, Abdou Youss...
BMCBI
2007
127views more  BMCBI 2007»
13 years 5 months ago
A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments
Background: With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across...
Hyungwon Choi, Ronglai Shen, Arul M. Chinnaiyan, D...
BMCBI
2007
138views more  BMCBI 2007»
13 years 5 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...
APBC
2004
138views Bioinformatics» more  APBC 2004»
13 years 6 months ago
Whole-Genome Functional Classification of Genes by Latent Semantic Analysis on Microarray Data
Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments. The resulti...
See-Kiong Ng, Zexuan Zhu, Yew-Soon Ong
BMCBI
2006
101views more  BMCBI 2006»
13 years 5 months ago
SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms
Background: The development of algorithms to infer the structure of gene regulatory networks based on expression data is an important subject in bioinformatics research. Validatio...
Tim Van den Bulcke, Koen Van Leemput, Bart Naudts,...