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EUROGP
2004
Springer
133views Optimization» more  EUROGP 2004»
15 years 3 months ago
Lymphoma Cancer Classification Using Genetic Programming with SNR Features
Lymphoma cancer classification with DNA microarray data is one of important problems in bioinformatics. Many machine learning techniques have been applied to the problem and produc...
Jin-Hyuk Hong, Sung-Bae Cho
BMCBI
2007
139views more  BMCBI 2007»
14 years 9 months ago
Significance analysis of microarray transcript levels in time series experiments
Background: Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over ...
Barbara Di Camillo, Gianna Toffolo, Sreekumaran K....
BMCBI
2008
167views more  BMCBI 2008»
14 years 9 months ago
Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments
Background: Most microarray experiments are carried out with the purpose of identifying genes whose expression varies in relation with specific conditions or in response to enviro...
Stefano Parodi, Vito Pistoia, Marco Muselli
RR
2010
Springer
14 years 8 months ago
Redundancy Elimination on RDF Graphs in the Presence of Rules, Constraints, and Queries
Based on practical observations on rule-based inference on RDF data, we study the problem of redundancy elimination on RDF graphs in the presence of rules (in the form of Datalog r...
Reinhard Pichler, Axel Polleres, Sebastian Skritek...
CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
15 years 2 months ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...