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» AffyMiner: mining differentially expressed genes and biologi...
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BMCBI
2006
109views more  BMCBI 2006»
13 years 7 months ago
Integrated analysis of gene expression by association rules discovery
Background: Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditi...
Pedro Carmona-Saez, Monica Chagoyen, Andrés...
BMCBI
2010
158views more  BMCBI 2010»
13 years 7 months ago
Validation of differential gene expression algorithms: Application comparing fold-change estimation to hypothesis testing
Background: Sustained research on the problem of determining which genes are differentially expressed on the basis of microarray data has yielded a plethora of statistical algorit...
Corey M. Yanofsky, David R. Bickel
BMCBI
2008
124views more  BMCBI 2008»
13 years 7 months ago
Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease
Background: Comparative analysis of expression microarray studies is difficult due to the large influence of technical factors on experimental outcome. Still, the identified diffe...
Rob Jelier, Peter A. C. 't Hoen, Ellen Sterrenburg...
KDD
2008
ACM
206views Data Mining» more  KDD 2008»
14 years 8 months ago
Identifying biologically relevant genes via multiple heterogeneous data sources
Selection of genes that are differentially expressed and critical to a particular biological process has been a major challenge in post-array analysis. Recent development in bioin...
Zheng Zhao, Jiangxin Wang, Huan Liu, Jieping Ye, Y...
BMCBI
2007
152views more  BMCBI 2007»
13 years 7 months ago
Difference-based clustering of short time-course microarray data with replicates
Background: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain know...
Jihoon Kim, Ju Han Kim