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» Gene set analysis using principal components
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BMCBI
2010
216views more  BMCBI 2010»
13 years 5 months ago
Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies
Background: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors f...
Bo Chen, Minhua Chen, John William Paisley, Aimee ...
BIOCOMP
2006
14 years 5 days ago
A Heuristic Approach to Scoring Gene Clustering Algorithms
In the past decades, many clustering algorithms have been proposed for the analysis of gene expression data, but little guidance is available to help choose among them. Given the ...
Longde Yin, Chun-Hsi Huang
FGR
2008
IEEE
195views Biometrics» more  FGR 2008»
14 years 5 months ago
Regularized active shape model for shape alignment
Active shape model (ASM) statistically represents a shape by a set of well-defined landmark points and models object variations using principal component analysis (PCA). However, ...
Ran He, Zhen Lei, Xiaotong Yuan, Stan Z. Li
ICIAP
2003
ACM
14 years 4 months ago
PCA vs low resolution images in face verification
Principal Components Analysis (PCA) has been one of the most applied methods for face verification using only 2D information, in fact, PCA is practically the method of choice for ...
Cristina Conde, Antonio Ruiz, Enrique Cabello
NIPS
2004
14 years 4 days ago
Machine Learning Applied to Perception: Decision Images for Gender Classification
We study gender discrimination of human faces using a combination of psychophysical classification and discrimination experiments together with methods from machine learning. We r...
Felix A. Wichmann, Arnulf B. A. Graf, Eero P. Simo...