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BMCBI
2005
140views more  BMCBI 2005»
13 years 5 months ago
Dissecting systems-wide data using mixture models: application to identify affected cellular processes
Background: Functional analysis of data from genome-scale experiments, such as microarrays, requires an extensive selection of differentially expressed genes. Under many condition...
J. Peter Svensson, Renée X. de Menezes, Ing...
BMCBI
2010
154views more  BMCBI 2010»
13 years 5 months ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...
CSB
2004
IEEE
106views Bioinformatics» more  CSB 2004»
13 years 8 months ago
A Theoretical Analysis of Gene Selection
A great deal of recent research has focused on the challenging task of selecting differentially expressed genes from microarray data (`gene selection'). Numerous gene selecti...
Sach Mukherjee, Stephen J. Roberts
BMCBI
2008
99views more  BMCBI 2008»
13 years 5 months ago
Ranking analysis of F-statistics for microarray data
Background: Microarray technology provides an efficient means for globally exploring physiological processes governed by the coordinated expression of multiple genes. However, ide...
Yuan-De Tan, Myriam Fornage, Hongyan Xu
BMCBI
2004
150views more  BMCBI 2004»
13 years 4 months ago
Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data
Background: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals ...
Dietmar E. Martin, Philippe Demougin, Michael N. H...