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» Unfolding of Microarray Data
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BIOCOMP
2006
13 years 9 months ago
Learning Genetic and Gene Bayesian Networks with Hidden Variables: Bilayer Verification Algorithm
To improve the recovery of gene-gene and marker-gene (eQTL) interaction networks from microarray and genetic data, we propose a new procedure for learning Bayesian networks. This a...
Jason E. Aten
BMEI
2009
IEEE
13 years 9 months ago
An Improved Probabilistic Model for Finding Differential Gene Expression
Abstract--Finding differentially expressed genes is a fundamental objective of a microarray experiment. Recently proposed method, PPLR, considers the probe-level measurement error ...
Li Zhang, Xuejun Liu
HPDC
2010
IEEE
13 years 9 months ago
Optimization of a parallel permutation testing function for the SPRINT R package
The statistical language R and Bioconductor package are favoured by many biostatisticians for processing microarray data. The amount of data produced by these analyses has reached...
Savvas Petrou, Terence M. Sloan, Muriel Mewissen, ...
APIN
2010
108views more  APIN 2010»
13 years 8 months ago
A low variance error boosting algorithm
Abstract. This paper introduces a robust variant of AdaBoost, cwAdaBoost, that uses weight perturbation to reduce variance error, and is particularly effective when dealing with da...
Ching-Wei Wang, Andrew Hunter
BIOINFORMATICS
2006
96views more  BIOINFORMATICS 2006»
13 years 7 months ago
Joint estimation of calibration and expression for high-density oligonucleotide arrays
Motivation: The need for normalization in microarray experiments has been well documented in the literature. Currently, most analysis methods treat normalization and analysis as a...
Ann L. Oberg, Douglas W. Mahoney, Karla V. Ballman...