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» Analysis of Variance for Gene Expression Microarray Data
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BMEI
2008
IEEE
15 years 8 months ago
Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...
Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wun...
IDA
2005
Springer
15 years 11 months ago
Bayesian Networks Learning for Gene Expression Datasets
DNA arrays yield a global view of gene expression and can be used to build genetic networks models, in order to study relations between genes. Literature proposes Bayesian network ...
Giacomo Gamberoni, Evelina Lamma, Fabrizio Riguzzi...
BMCBI
2010
158views more  BMCBI 2010»
15 years 6 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
2007
133views more  BMCBI 2007»
15 years 6 months ago
GenMAPP 2: new features and resources for pathway analysis
Background: Microarray technologies have evolved rapidly, enabling biologists to quantify genome-wide levels of gene expression, alternative splicing, and sequence variations for ...
Nathan Salomonis, Kristina Hanspers, Alexander C. ...
ICCS
2009
Springer
15 years 4 months ago
Gene Specific Co-regulation Discovery: An Improved Approach
Abstract. Discovering gene co-regulatory relationships is a new but important research problem in DNA microarray data analysis. The problem of gene specific co-regulation discovery...
Ji Zhang, Qing Liu, Kai Xu 0003