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BMCBI
2008
159views more  BMCBI 2008»
13 years 7 months ago
Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
Hongya Zhao, Kwok-Leung Chan, Lee-Ming Cheng, Hong...
BMCBI
2008
142views more  BMCBI 2008»
13 years 7 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
RECOMB
2002
Springer
14 years 8 months ago
A bayesian approach to transcript estimation from gene array data: the BEAM technique
We present a new statistically optimal approach to estimate transcript levels and ratios from one or more gene array experiments. The Bayesian Estimation of Array Measurements (BE...
Ron O. Dror, Jonathan G. Murnick, Nicola A. Rinald...
BMCBI
2007
144views more  BMCBI 2007»
13 years 7 months ago
Robust regression for periodicity detection in non-uniformly sampled time-course gene expression data
Background: In practice many biological time series measurements, including gene microarrays, are conducted at time points that seem to be interesting in the biologist's opin...
Miika Ahdesmäki, Harri Lähdesmäki, ...
BMCBI
2007
163views more  BMCBI 2007»
13 years 7 months ago
Use of genomic DNA control features and predicted operon structure in microarray data analysis: ArrayLeaRNA - a Bayesian approac
Background: Microarrays are widely used for the study of gene expression; however deciding on whether observed differences in expression are significant remains a challenge. Resul...
Carmen Pin, Mark Reuter