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» A cluster validity framework for genome expression data
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BMCBI
2007
194views more  BMCBI 2007»
15 years 2 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
BMCBI
2007
123views more  BMCBI 2007»
15 years 1 months ago
Robust clustering in high dimensional data using statistical depths
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...
Yuanyuan Ding, Xin Dang, Hanxiang Peng, Dawn Wilki...
GCB
2003
Springer
105views Biometrics» more  GCB 2003»
15 years 7 months ago
In silico prediction of UTR repeats using clustered EST data
Clustering of EST data is a method for the non-redundant representation of an organisms transcriptome. During clustering of large amounts of EST data, usually some large clusters ...
Stefan A. Rensing, Daniel Lang, Ralf Reski
BMCBI
2010
193views more  BMCBI 2010»
14 years 9 months ago
Mayday - integrative analytics for expression data
Background: DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the ge...
Florian Battke, Stephan Symons, Kay Nieselt
NAR
2000
117views more  NAR 2000»
15 years 1 months ago
The TIGR Gene Indices: reconstruction and representation of expressed gene sequences
Expressed sequence tags (ESTs) have provided a first glimpse of the collection of transcribed sequences in a variety of organisms. However, a careful analysis of this sequence dat...
John Quackenbush, Feng Liang, Ingeborg Holt, Geo P...