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» Comparative analysis of biclustering algorithms
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BMCBI
2010
118views more  BMCBI 2010»
13 years 8 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
BMCBI
2007
146views more  BMCBI 2007»
13 years 8 months ago
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
BMCBI
2010
89views more  BMCBI 2010»
13 years 8 months ago
Semi-automatic identification of punching areas for tissue microarray building: the tubular breast cancer pilot study
Background: Tissue MicroArray technology aims to perform immunohistochemical staining on hundreds of different tissue samples simultaneously. It allows faster analysis, considerab...
Federica Viti, Ivan Merelli, Mieke Timmermans, Mic...
BMCBI
2007
128views more  BMCBI 2007»
13 years 7 months ago
Combining classifiers to predict gene function in Arabidopsis thaliana using large-scale gene expression measurements
Background: Arabidopsis thaliana is the model species of current plant genomic research with a genome size of 125 Mb and approximately 28,000 genes. The function of half of these ...
Hui Lan, Rachel Carson, Nicholas J. Provart, Antho...
PRL
2008
78views more  PRL 2008»
13 years 7 months ago
Retrieving scale from quasi-stationary images
(204 words) We have developed a novel method to derive scale information from quasi-stationary images, which relies on a rotation-guided multi-scale analysis of features derived fr...
Piotr W. Mirowski, Daniel M. Tetzlaff