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BMCBI
2010
154views more  BMCBI 2010»
15 years 4 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 ...
BMCBI
2006
86views more  BMCBI 2006»
15 years 4 months ago
Identification of QTLs controlling gene expression networks defined a priori
Background: Gene expression microarrays allow the quantification of transcript accumulation for many or all genes in a genome. This technology has been utilized for a range of inv...
Daniel J. Kliebenstein, Marilyn A. L. West, Hans v...
132
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RECOMB
2005
Springer
16 years 4 months ago
Causal Inference of Regulator-Target Pairs by Gene Mapping of Expression Phenotypes
Background: Correlations between polymorphic markers and observed phenotypes provide the basis for mapping traits in quantitative genetics. When the phenotype is gene expression, ...
David Kulp, Manjunatha Jagalur
BMCBI
2007
159views more  BMCBI 2007»
15 years 4 months ago
Detecting differential expression in microarray data: comparison of optimal procedures
Background: Many procedures for finding differentially expressed genes in microarray data are based on classical or modified t-statistics. Due to multiple testing considerations, ...
Elena Perelman, Alexander Ploner, Stefano Calza, Y...
AOSD
2005
ACM
15 years 10 months ago
An expressive aspect language for system applications with Arachne
C applications, in particular those using operating system level services, frequently comprise multiple crosscutting concerns: network protocols and security are typical examples ...
Rémi Douence, Thomas Fritz, Nicolas Loriant...