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» Improving gene set analysis of microarray data by SAM-GS
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BIOINFORMATICS
2007
137views more  BIOINFORMATICS 2007»
13 years 7 months ago
Annotation-based distance measures for patient subgroup discovery in clinical microarray studies
: Background Clustering algorithms are widely used in the analysis of microarray data. In clinical studies, they are often applied to find groups of co-regulated genes. Clustering...
Claudio Lottaz, Joern Toedling, Rainer Spang
BMCBI
2011
13 years 2 months ago
Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in i
Background: In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focuse...
Paolo G. V. Martini, Davide Risso, Gabriele Sales,...
BMCBI
2006
131views more  BMCBI 2006»
13 years 7 months ago
SIMAGE: simulation of DNA-microarray gene expression data
Background: Simulation of DNA-microarray data serves at least three purposes: (i) optimizing the design of an intended DNA microarray experiment, (ii) comparing existing pre-proce...
Casper J. Albers, Ritsert C. Jansen, Jan Kok, Osca...
BMCBI
2010
130views more  BMCBI 2010»
13 years 7 months ago
Knowledge-guided gene ranking by coordinative component analysis
Background: In cancer, gene networks and pathways often exhibit dynamic behavior, particularly during the process of carcinogenesis. Thus, it is important to prioritize those gene...
Chen Wang, Jianhua Xuan, Huai Li, Yue Wang, Ming Z...
ICASSP
2009
IEEE
14 years 2 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...