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BMCBI
2006
86views more  BMCBI 2006»
13 years 7 months ago
The impact of sample imbalance on identifying differentially expressed genes
Background: Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the p...
Kun Yang, Jianzhong Li, Hong Gao
BMCBI
2007
194views more  BMCBI 2007»
13 years 7 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
BMCBI
2006
122views more  BMCBI 2006»
13 years 7 months ago
A multivariate prediction model for microarray cross-hybridization
Background: Expression microarray analysis is one of the most popular molecular diagnostic techniques in the post-genomic era. However, this technique faces the fundamental proble...
Yian A. Chen, Cheng-Chung Chou, Xinghua Lu, Elizab...
IDA
2005
Springer
14 years 1 months ago
Bayesian Networks Learning for Gene Expression Datasets
DNA arrays yield a global view of gene expression and can be used to build genetic networks models, in order to study relations between genes. Literature proposes Bayesian network ...
Giacomo Gamberoni, Evelina Lamma, Fabrizio Riguzzi...
BMCBI
2005
140views more  BMCBI 2005»
13 years 7 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...