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» Smoothing Gene Expression Using Biological Networks
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CSDA
2007
151views more  CSDA 2007»
13 years 8 months ago
Robust semiparametric mixing for detecting differentially expressed genes in microarray experiments
An important goal of microarray studies is the detection of genes that show significant changes in observed expressions when two or more classes of biological samples such as tre...
Marco Alfò, Alessio Farcomeni, Luca Tardell...
ITSSA
2006
109views more  ITSSA 2006»
13 years 8 months ago
Gene Expression Analysis in Multi-Agent Environment
Abstract. This paper presents a multi-agent approach to gene expression analysis and illustrates the working steps using real dataset produced from a microarray experiment. The ana...
H. C. Lam, M. Vazquez, B. Juneja, Scott C. Fahrenk...
JIB
2010
107views more  JIB 2010»
13 years 3 months ago
Integration of -omics data and networks for biomedical research with VANTED
Increasingly, research focus in the fields of biology and medicine moves from the investigation of single phenomena to the analysis of complex cause and effect relationships. The ...
Christian Klukas, Falk Schreiber
BMCBI
2006
133views more  BMCBI 2006»
13 years 9 months ago
Web-based analysis of the mouse transcriptome using Genevestigator
Background: Gene function analysis often requires a complex and laborious sequence of laboratory and computer-based experiments. Choosing an effective experimental design generall...
Oliver Laule, Matthias Hirsch-Hoffmann, Tomas Hruz...
ISMB
2000
13 years 10 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...