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» Gene set analysis using principal components
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AAAI
2004
13 years 9 months ago
Bayesian Inference on Principal Component Analysis Using Reversible Jump Markov Chain Monte Carlo
Based on the probabilistic reformulation of principal component analysis (PCA), we consider the problem of determining the number of principal components as a model selection prob...
Zhihua Zhang, Kap Luk Chan, James T. Kwok, Dit-Yan...
BMCBI
2008
135views more  BMCBI 2008»
13 years 8 months ago
Knowledge-guided multi-scale independent component analysis for biomarker identification
Background: Many statistical methods have been proposed to identify disease biomarkers from gene expression profiles. However, from gene expression profile data alone, statistical...
Li Chen, Jianhua Xuan, Chen Wang, Ie-Ming Shih, Yu...
BMCBI
2006
203views more  BMCBI 2006»
13 years 8 months ago
Independent component analysis reveals new and biologically significant structures in micro array data
Background: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem...
Attila Frigyesi, Srinivas Veerla, David Lindgren, ...
NCA
2007
IEEE
13 years 7 months ago
Handling of incomplete data sets using ICA and SOM in data mining
Based on independent component analysis (ICA) and self-organizing maps (SOM), this paper proposes an ISOM-DH model for the incomplete data’s handling in data mining. Under these ...
Hongyi Peng, Siming Zhu
PRL
2006
225views more  PRL 2006»
13 years 8 months ago
A straight line detection using principal component analysis
A straight line detection algorithm is presented. The algorithm separates row and column edges from edge image using their primitive shapes. The edges are labeled, and the princip...
Yun-Seok Lee, Han-Suh Koo, Chang-Sung Jeong