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» Clustering cancer gene expression data: a comparative study
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BMCBI
2007
148views more  BMCBI 2007»
15 years 6 months ago
Computation of significance scores of unweighted Gene Set Enrichment Analyses
Background: Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for in...
Andreas Keller, Christina Backes, Hans-Peter Lenho...
BMCBI
2010
153views more  BMCBI 2010»
15 years 6 months ago
GOAL: A software tool for assessing biological significance of genes groups
Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
BMCBI
2004
75views more  BMCBI 2004»
15 years 6 months ago
Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes
Background: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very f...
Hongying Jiang, Youping Deng, Huann-Sheng Chen, Li...
KDD
2004
ACM
314views Data Mining» more  KDD 2004»
16 years 6 months ago
Assessment of discretization techniques for relevant pattern discovery from gene expression data
In the domain of gene expression data analysis, various researchers have recently emphasized the promising application of pattern discovery techniques like association rule mining...
Ruggero G. Pensa, Claire Leschi, Jéré...
BMCBI
2010
115views more  BMCBI 2010»
15 years 6 months ago
Assessment and optimisation of normalisation methods for dual-colour antibody microarrays
Background: Recent advances in antibody microarray technology have made it possible to measure the expression of hundreds of proteins simultaneously in a competitive dual-colour a...
Martin Sill, Christoph Schroder, Jörg D. Hohe...