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» Determining gene expression on a single pair of microarrays
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NIPS
2004
13 years 9 months ago
PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data
We propose a "soft greedy" learning algorithm for building small conjunctions of simple threshold functions, called rays, defined on single real-valued attributes. We al...
Mario Marchand, Mohak Shah
BMCBI
2010
165views more  BMCBI 2010»
13 years 7 months ago
Bayesian integrated modeling of expression data: a case study on RhoG
Background: DNA microarrays provide an efficient method for measuring activity of genes in parallel and even covering all the known transcripts of an organism on a single array. T...
Rashi Gupta, Dario Greco, Petri Auvinen, Elja Arja...
BMCBI
2007
140views more  BMCBI 2007»
13 years 7 months ago
Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets
Background: Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles...
Michael Gormley, William Dampier, Adam Ertel, Bilg...
BMCBI
2005
97views more  BMCBI 2005»
13 years 7 months ago
Modelling the correlation between the activities of adjacent genes in drosophila
Background: Correlation between the expression levels of genes which are located close to each other on the genome has been found in various organisms, including yeast, drosophila...
Helene H. Thygesen, Aeilko H. Zwinderman
BMCBI
2006
134views more  BMCBI 2006»
13 years 7 months ago
An approach for clustering gene expression data with error information
Background: Clustering of gene expression patterns is a well-studied technique for elucidating trends across large numbers of transcripts and for identifying likely co-regulated g...
Brian Tjaden