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» Analysis of variance components in gene expression data
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ICDM
2002
IEEE
158views Data Mining» more  ICDM 2002»
15 years 2 months ago
Adaptive dimension reduction for clustering high dimensional data
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...
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
BMCBI
2006
107views more  BMCBI 2006»
14 years 10 months ago
Evaluation of methods for oligonucleotide array data via quantitative real-time PCR
Background: There are currently many different methods for processing and summarizing probelevel data from Affymetrix oligonucleotide arrays. It is of great interest to validate t...
Li-Xuan Qin, Richard P. Beyer, Francesca N. Hudson...
BMCBI
2007
131views more  BMCBI 2007»
14 years 10 months ago
FUNC: a package for detecting significant associations between gene sets and ontological annotations
Background: Genome-wide expression, sequence and association studies typically yield large sets of gene candidates, which must then be further analysed and interpreted. Informatio...
Kay Prüfer, Bjoern Muetzel, Hong Hai Do, Gunt...
ECCV
2002
Springer
15 years 11 months ago
Robust Parameterized Component Analysis
Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...
Fernando De la Torre, Michael J. Black