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» Gene set analysis for longitudinal gene expression data
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BMCBI
2004
205views more  BMCBI 2004»
13 years 8 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
BMCBI
2008
125views more  BMCBI 2008»
13 years 9 months ago
Exploration and visualization of gene expression with neuroanatomy in the adult mouse brain
Background: Spatially mapped large scale gene expression databases enable quantitative comparison of data measurements across genes, anatomy, and phenotype. In most ongoing effort...
Christopher Lau, Lydia Ng, Carol Thompson, Sayan D...
ICDE
2008
IEEE
195views Database» more  ICDE 2008»
14 years 10 months ago
Scalable Rule-Based Gene Expression Data Classification
Abstract-- Current state-of-the-art association rule-based classifiers for gene expression data operate in two phases: (i) Association rule mining from training data followed by (i...
Mark A. Iwen, Willis Lang, Jignesh M. Patel
BMCBI
2006
122views more  BMCBI 2006»
13 years 9 months ago
A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets
Background: Gene selection is an important step when building predictors of disease state based on gene expression data. Gene selection generally improves performance and identifi...
Carmen Lai, Marcel J. T. Reinders, Laura J. van't ...
TNN
2008
105views more  TNN 2008»
13 years 8 months ago
Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
Shuiwang Ji, Jieping Ye