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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2008
98views more  BMCBI 2008»
15 years 12 hour 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»
14 years 11 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»
14 years 11 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 6 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 10 hour 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...