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» Clustering cancer gene expression data: a comparative study
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BMCBI
2006
158views more  BMCBI 2006»
15 years 6 months ago
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...
ICIC
2009
Springer
16 years 22 days ago
Ensemble Classifiers Based on Kernel PCA for Cancer Data Classification
Now the classification of different tumor types is of great importance in cancer diagnosis and drug discovery. It is more desirable to create an optimal ensemble for data analysis ...
Jin Zhou, Yuqi Pan, Yuehui Chen, Yang Liu
BIOINFORMATICS
2007
137views more  BIOINFORMATICS 2007»
15 years 6 months ago
Annotation-based distance measures for patient subgroup discovery in clinical microarray studies
: Background Clustering algorithms are widely used in the analysis of microarray data. In clinical studies, they are often applied to find groups of co-regulated genes. Clustering...
Claudio Lottaz, Joern Toedling, Rainer Spang
TCBB
2008
107views more  TCBB 2008»
15 years 6 months ago
Coclustering of Human Cancer Microarrays Using Minimum Sum-Squared Residue Coclustering
It is a consensus in microarray analysis that identifying potential local patterns, characterized by coherent groups of genes and conditions, may shed light on the discovery of pre...
Hyuk Cho, Inderjit S. Dhillon
BMCBI
2006
165views more  BMCBI 2006»
15 years 6 months ago
Validation and functional annotation of expression-based clusters based on gene ontology
Background: The biological interpretation of large-scale gene expression data is one of the paramount challenges in current bioinformatics. In particular, placing the results in t...
Ralf Steuer, Peter Humburg, Joachim Selbig