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» Landscape of Clustering Algorithms
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BMCBI
2010
118views more  BMCBI 2010»
15 years 6 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
2008
87views more  BMCBI 2008»
15 years 6 months ago
Protein structure search and local structure characterization
Background: Structural similarities among proteins can provide valuable insight into their functional mechanisms and relationships. As the number of available three-dimensional (3...
Shih-Yen Ku, Yuh-Jyh Hu
BMCBI
2007
146views more  BMCBI 2007»
15 years 6 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
2007
99views more  BMCBI 2007»
15 years 6 months ago
Statistical significance of cis-regulatory modules
Background: It is becoming increasingly important for researchers to be able to scan through large genomic regions for transcription factor binding sites or clusters of binding si...
Dustin E. Schones, Andrew D. Smith, Michael Q. Zha...
BMCBI
2008
104views more  BMCBI 2008»
15 years 6 months ago
Evolutionary Pareto-optimization of stably folding peptides
Background: As a rule, peptides are more flexible and unstructured than proteins with their substantial stabilizing hydrophobic cores. Nevertheless, a few stably folding peptides ...
Wolfram Gronwald, Tim Hohm, Daniel Hoffmann