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» Prediction on Spike Data Using Kernel Algorithms
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BMCBI
2011
13 years 4 months ago
Motif-guided sparse decomposition of gene expression data for regulatory module identification
Background: Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for e...
Ting Gong, Jianhua Xuan, Li Chen, Rebecca B. Riggi...
DCC
2003
IEEE
14 years 8 months ago
PPM Model Cleaning
The Prediction by Partial Matching (PPM) algorithm uses a cumulative frequency count of input symbols in different contexts to estimate their probability distribution. Excellent c...
Milenko Drinic, Darko Kirovski, Miodrag Potkonjak
BMCBI
2006
151views more  BMCBI 2006»
13 years 9 months ago
Modeling Sage data with a truncated gamma-Poisson model
Background: Serial Analysis of Gene Expressions (SAGE) produces gene expression measurements on a discrete scale, due to the finite number of molecules in the sample. This means t...
Helene H. Thygesen, Aeilko H. Zwinderman
BMCBI
2005
151views more  BMCBI 2005»
13 years 9 months ago
stam - a Bioconductor compliant R package for structured analysis of microarray data
Background: Genome wide microarray studies have the potential to unveil novel disease entities. Clinically homogeneous groups of patients can have diverse gene expression profiles...
Claudio Lottaz, Rainer Spang
BMCBI
2007
91views more  BMCBI 2007»
13 years 9 months ago
A machine learning approach for the identification of odorant binding proteins from sequence-derived properties
Background: Odorant binding proteins (OBPs) are believed to shuttle odorants from the environment to the underlying odorant receptors, for which they could potentially serve as od...
Ganesan Pugalenthi, E. Ke Tang, Ponnuthurai N. Sug...