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» Modeling Microarray Data: Interpreting and communicating the...
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BIODATAMINING
2008
135views more  BIODATAMINING 2008»
13 years 9 months ago
Fast Gene Ontology based clustering for microarray experiments
Background: Analysis of a microarray experiment often results in a list of hundreds of diseaseassociated genes. In order to suggest common biological processes and functions for t...
Kristian Ovaska, Marko Laakso, Sampsa Hautaniemi
BMCBI
2007
154views more  BMCBI 2007»
13 years 9 months ago
Inferring biological networks with output kernel trees
Background: Elucidating biological networks between proteins appears nowadays as one of the most important challenges in systems biology. Computational approaches to this problem ...
Pierre Geurts, Nizar Touleimat, Marie Dutreix, Flo...
BMCBI
2005
212views more  BMCBI 2005»
13 years 9 months ago
PAGE: Parametric Analysis of Gene Set Enrichment
Background: Gene set enrichment analysis (GSEA) is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes i...
Seon-Young Kim, David J. Volsky
JBI
2008
159views Bioinformatics» more  JBI 2008»
13 years 9 months ago
SEGS: Search for enriched gene sets in microarray data
Gene Ontology (GO) terms are often used to interpret the results of microarray experiments. The most common approach is to perform Fisher's exact tests to find gene sets anno...
Igor Trajkovski, Nada Lavrac, Jakub Tolar
BMCBI
2007
186views more  BMCBI 2007»
13 years 9 months ago
GeneBins: a database for classifying gene expression data, with application to plant genome arrays
Background: To interpret microarray experiments, several ontological analysis tools have been developed. However, current tools are limited to specific organisms. Results: We deve...
Nicolas Goffard, Georg Weiller