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BMCBI
2010
144views more  BMCBI 2010»
15 years 4 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
16 years 6 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»
15 years 4 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»
15 years 4 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»
15 years 4 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