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BMCBI
2006
82views more  BMCBI 2006»
13 years 7 months ago
Profiling alternatively spliced mRNA isoforms for prostate cancer classification
Background: Prostate cancer is one of the leading causes of cancer illness and death among men in the United States and world wide. There is an urgent need to discover good biomar...
Chaolin Zhang, Hai-Ri Li, Jian-Bing Fan, Jessica W...
BMCBI
2008
128views more  BMCBI 2008»
13 years 7 months ago
Improving the prediction accuracy in classification using the combined data sets by ranks of gene expressions
Background: The information from different data sets experimented under different conditions may be inconsistent even though they are performed with the same research objectives. ...
Ki-Yeol Kim, Dong Hyuk Ki, Hei-Cheul Jeung, Hyun C...
BMCBI
2010
118views more  BMCBI 2010»
13 years 7 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
114views more  BMCBI 2007»
13 years 7 months ago
Large scale statistical inference of signaling pathways from RNAi and microarray data
Background: The advent of RNA interference techniques enables the selective silencing of biologically interesting genes in an efficient way. In combination with DNA microarray tec...
Holger Fröhlich, Mark Fellmann, Holger Sü...
CCE
2005
13 years 7 months ago
Selecting maximally informative genes
Microarray experiments are emerging as one of the main driving forces in modern biology. By allowing the simultaneous monitoring of the expression of the entire genome for a given...
Ioannis P. Androulakis