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» Evaluation of clustering algorithms for gene expression data
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156
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BMCBI
2006
126views more  BMCBI 2006»
15 years 6 months ago
Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass ge
Background: Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gen...
Chia Huey Ooi, Madhu Chetty, Shyh Wei Teng
BMCBI
2011
15 years 1 months ago
Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms
Background: The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade...
Andrew T. Milnthorpe, Mikhail Soloviev
KDD
2004
ACM
302views Data Mining» more  KDD 2004»
16 years 6 months ago
Redundancy based feature selection for microarray data
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Lei Yu, Huan Liu
BMCBI
2010
92views more  BMCBI 2010»
15 years 6 months ago
Integrating gene expression and GO classification for PCA by preclustering
Background: Gene expression data can be analyzed by summarizing groups of individual gene expression profiles based on GO annotation information. The mean expression profile per g...
Jorn R. de Haan, Ester Piek, René C. van Sc...
215
Voted
BMCBI
2007
194views more  BMCBI 2007»
15 years 6 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung