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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2008
98views more  BMCBI 2008»
15 years 1 months ago
Empirical Bayes models for multiple probe type microarrays at the probe level
Background: When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are...
Magnus Åstrand, Petter Mostad, Mats Rudemo
BMCBI
2005
121views more  BMCBI 2005»
15 years 1 months ago
Evaluation of gene importance in microarray data based upon probability of selection
Background: Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many import...
Li M. Fu, Casey S. Fu-Liu
BMCBI
2005
223views more  BMCBI 2005»
15 years 1 months ago
Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling
Background: The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in anim...
Hong Fang, Weida Tong, Roger Perkins, Leming M. Sh...
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
15 years 7 months ago
A multi-objective approach to discover biclusters in microarray data
The main motivation for using a multi–objective evolutionary algorithm for finding biclusters in gene expression data is motivated by the fact that when looking for biclusters ...
Federico Divina, Jesús S. Aguilar-Ruiz
BMCBI
2007
169views more  BMCBI 2007»
15 years 1 months ago
Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and i
Background: Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targ...
Abdallah Sayyed-Ahmad, Kagan Tuncay, Peter J. Orto...