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» Class discovery in gene expression data
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BMCBI
2006
165views more  BMCBI 2006»
13 years 7 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin
BMCBI
2008
179views more  BMCBI 2008»
13 years 7 months ago
Building pathway clusters from Random Forests classification using class votes
Background: Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bri...
Herbert Pang, Hongyu Zhao
BMCBI
2010
155views more  BMCBI 2010»
13 years 7 months ago
A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer
Background: In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of...
Fan Shi, Christopher Leckie, Geoff MacIntyre, Izha...
FUIN
2007
109views more  FUIN 2007»
13 years 7 months ago
Unifying Framework for Rule Semantics: Application to Gene Expression Data
Abstract. The notion of rules is very popular and appears in different flavors, for example as association rules in data mining or as functional dependencies in databases. Their s...
Marie Agier, Jean-Marc Petit, Einoshin Suzuki
AIIA
2009
Springer
14 years 2 months ago
Ontology-Driven Co-clustering of Gene Expression Data
Abstract. The huge volume of gene expression data produced by microarrays and other high-throughput techniques has encouraged the development of new computational techniques to eva...
Francesca Cordero, Ruggero G. Pensa, Alessia Visco...