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» A cluster validity framework for genome expression data
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BMCBI
2010
147views more  BMCBI 2010»
13 years 6 months ago
baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data
Background: High throughput sequencing has become an important technology for studying expression levels in many types of genomic, and particularly transcriptomic, data. One key w...
Thomas J. Hardcastle, Krystyna A. Kelly
CGF
2008
142views more  CGF 2008»
13 years 6 months ago
Visualizing Genome Expression and Regulatory Network Dynamics in Genomic and Metabolic Context
DNA microarrays are used to measure the expression levels of thousands of genes simultaneously. In a time series experiment, the gene expressions are measured as a function of tim...
Michel A. Westenberg, Sacha A. F. T. van Hijum, Os...
ITA
2006
167views Communications» more  ITA 2006»
13 years 6 months ago
Characterization of lung tumor subtypes through gene expression cluster validity assessment
The problem of assessing the reliability of clusters patients identified by clustering algorithms is crucial to estimate the significance of subclasses of diseases detectable at b...
Giorgio Valentini, Francesca Ruffino
BMCBI
2007
227views more  BMCBI 2007»
13 years 6 months ago
Growing functional modules from a seed protein via integration of protein interaction and gene expression data
Background: Nowadays modern biology aims at unravelling the strands of complex biological structures such as the protein-protein interaction (PPI) networks. A key concept in the o...
Ioannis A. Maraziotis, Konstantina Dimitrakopoulou...
BMCBI
2010
214views more  BMCBI 2010»
13 years 6 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper