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» Clustering cancer gene expression data: a comparative study
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BMCBI
2011
15 years 24 days ago
Sequential Interim Analyses of Survival Data in DNA Microarray Experiments
Background: Discovery of biomarkers that are correlated with therapy response and thus with survival is an important goal of medical research on severe diseases, e.g. cancer. Freq...
Andreas Leha, Tim Beißbarth, Klaus Jung
BMCBI
2006
155views more  BMCBI 2006»
15 years 6 months ago
A powerful method for detecting differentially expressed genes from GeneChip arrays that does not require replicates
Background: Studies of differential expression that use Affymetrix GeneChip arrays are often carried out with a limited number of replicates. Reasons for this include financial co...
Anne-Mette K. Hein, Sylvia Richardson
BMCBI
2006
119views more  BMCBI 2006»
15 years 6 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs
BMCBI
2005
103views more  BMCBI 2005»
15 years 6 months ago
Quadratic regression analysis for gene discovery and pattern recognition for non-cyclic short time-course microarray experiments
Background: Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage o...
Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V...
BMCBI
2008
115views more  BMCBI 2008»
15 years 6 months ago
Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data
Background: Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differ...
Sudhakar Jonnalagadda, Rajagopalan Srinivasan