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BMCBI
2010
144views more  BMCBI 2010»
14 years 10 months ago
Super-sparse principal component analyses for high-throughput genomic data
Background: Principal component analysis (PCA) has gained popularity as a method for the analysis of highdimensional genomic data. However, it is often difficult to interpret the ...
Donghwan Lee, Woojoo Lee, Youngjo Lee, Yudi Pawita...
CVPR
2008
IEEE
15 years 12 months ago
A unified framework for generalized Linear Discriminant Analysis
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...
Shuiwang Ji, Jieping Ye
TNN
2008
105views more  TNN 2008»
14 years 9 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
BMCBI
2006
182views more  BMCBI 2006»
14 years 10 months ago
AceTree: a tool for visual analysis of Caenorhabditis elegans embryogenesis
Background: The invariant lineage of the nematode Caenorhabditis elegans has potential as a powerful tool for the description of mutant phenotypes and gene expression patterns. We...
Thomas J. Boyle, Zhirong Bao, John I. Murray, Carl...
BMCBI
2007
78views more  BMCBI 2007»
14 years 10 months ago
Improved human disease candidate gene prioritization using mouse phenotype
Background: The majority of common diseases are multi-factorial and modified by genetically and mechanistically complex polygenic interactions and environmental factors. High-thro...
Jing Chen, Huan Xu, Bruce J. Aronow, Anil G. Jegga