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» Microarray Gene Expression Data Analysis
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BMCBI
2006
133views more  BMCBI 2006»
15 years 2 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...
106
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DAWAK
2005
Springer
15 years 8 months ago
Gene Expression Biclustering Using Random Walk Strategies
A biclustering algorithm, based on a greedy technique and enriched with a local search strategy to escape poor local minima, is proposed. The algorithm starts with an initial rando...
Fabrizio Angiulli, Clara Pizzuti
125
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GECCO
2000
Springer
123views Optimization» more  GECCO 2000»
15 years 6 months ago
Genomic computing: explanatory modelling for functional genomics
Many newly discovered genes are of unknown function. DNA microarrays are a method for determining the expression levels of all genes in an organism for which a complete genome seq...
Richard J. Gilbert, Jem J. Rowland, Douglas B. Kel...
168
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BMCBI
2006
150views more  BMCBI 2006»
15 years 2 months ago
Instance-based concept learning from multiclass DNA microarray data
Background: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as...
Daniel P. Berrar, Ian Bradbury, Werner Dubitzky
121
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BMCBI
2010
105views more  BMCBI 2010»
15 years 2 months ago
Effects of scanning sensitivity and multiple scan algorithms on microarray data quality
Background: Maximizing the utility of DNA microarray data requires optimization of data acquisition through selection of an appropriate scanner setting. To increase the amount of ...
Andrew Williams, Errol M. Thomson