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» Combinations of Weak Classifiers
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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
2010
125views more  BMCBI 2010»
13 years 8 months ago
Large-scale prediction of protein-protein interactions from structures
Background: The prediction of protein-protein interactions is an important step toward the elucidation of protein functions and the understanding of the molecular mechanisms insid...
Martial Hue, Michael Riffle, Jean-Philippe Vert, W...
BMCBI
2010
208views more  BMCBI 2010»
13 years 8 months ago
A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data
Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are common...
Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y....
BMCBI
2008
133views more  BMCBI 2008»
13 years 8 months ago
LocateP: Genome-scale subcellular-location predictor for bacterial proteins
Background: In the past decades, various protein subcellular-location (SCL) predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phob...
Miaomiao Zhou, Jos Boekhorst, Christof Francke, Ro...
BMCBI
2007
130views more  BMCBI 2007»
13 years 8 months ago
Exploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins
Background: Recognition of binding sites in proteins is a direct computational approach to the characterization of proteins in terms of biological and biochemical function. Residu...
Qiwen Dong, Xiaolong Wang, Lei Lin, Yi Guan