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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2006
216views more  BMCBI 2006»
15 years 6 months ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...
JMLR
2010
125views more  JMLR 2010»
15 years 1 months ago
On utility of gene set signatures in gene expression-based cancer class prediction
Machine learning methods that can use additional knowledge in their inference process are central to the development of integrative bioinformatics. Inclusion of background knowled...
Minca Mramor, Marko Toplak, Gregor Leban, Tomaz Cu...
CSB
2005
IEEE
146views Bioinformatics» more  CSB 2005»
15 years 12 months ago
Multi-Metric and Multi-Substructure Biclustering Analysis for Gene Expression Data
A good number of biclustering algorithms have been proposed for grouping gene expression data. Many of them have adopted matrix norms to define the similarity score of a bicluste...
Sun-Yuan Kung, Man-Wai Mak, Ilias Tagkopoulos
BMCBI
2010
114views more  BMCBI 2010»
15 years 6 months ago
Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray develop
Background: Microorganisms display vast diversity, and each one has its own set of genes, cell components and metabolic reactions. To assess their huge unexploited metabolic poten...
Sébastien Terrat, Eric Peyretaillade, Olivi...
CINQ
2004
Springer
116views Database» more  CINQ 2004»
15 years 10 months ago
Contribution to Gene Expression Data Analysis by Means of Set Pattern Mining
Abstract. One of the exciting scientific challenges in functional genomics concerns the discovery of biologically relevant patterns from gene expression data. For instance, it is e...
Ruggero G. Pensa, Jérémy Besson, C&e...