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» Classification of microarray data using gene networks
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113
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BMCBI
2007
126views more  BMCBI 2007»
15 years 2 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
142
Voted
BMCBI
2006
146views more  BMCBI 2006»
15 years 2 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara
122
Voted
RECOMB
2007
Springer
16 years 2 months ago
A Bayesian Model That Links Microarray mRNA Measurements to Mass Spectrometry Protein Measurements
Abstract. An important problem in biology is to understand correspondences between mRNA microarray levels and mass spectrometry peptide counts. Recently, a compendium of mRNA expre...
Anitha Kannan, Andrew Emili, Brendan J. Frey
118
Voted
BMCBI
2008
130views more  BMCBI 2008»
15 years 2 months ago
Function approximation approach to the inference of reduced NGnet models of genetic networks
Background: The inference of a genetic network is a problem in which mutual interactions among genes are deduced using time-series of gene expression patterns. While a number of m...
Shuhei Kimura, Katsuki Sonoda, Soichiro Yamane, Hi...
BMCBI
2007
112views more  BMCBI 2007»
15 years 2 months ago
Inferring biological functions and associated transcriptional regulators using gene set expression coherence analysis
Background: Gene clustering has been widely used to group genes with similar expression pattern in microarray data analysis. Subsequent enrichment analysis using predefined gene s...
Tae-Min Kim, Yeun-Jun Chung, Mun-Gan Rhyu, Myeong ...