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» Clustering gene expression patterns
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BMCBI
2010
172views more  BMCBI 2010»
14 years 4 months ago
Nonparametric identification of regulatory interactions from spatial and temporal gene expression data
Background: The correlation between the expression levels of transcription factors and their target genes can be used to infer interactions within animal regulatory networks, but ...
Anil Aswani, Soile V. E. Keränen, James Brown...
BMCBI
2008
133views more  BMCBI 2008»
14 years 10 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...
CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
15 years 3 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...
EVOW
2008
Springer
14 years 11 months ago
Detection of Quantitative Trait Associated Genes Using Cluster Analysis
Abstract. Many efforts have been involved in association study of quantitative phenotypes and expressed genes. The key issue is how to efficiently identify phenotype-associated gen...
Zhenyu Jia, Sha Tang, Dan Mercola, Shizhong Xu
BMCBI
2006
173views more  BMCBI 2006»
14 years 10 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen