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BMCBI
2005
112views more  BMCBI 2005»
13 years 7 months ago
Visualization methods for statistical analysis of microarray clusters
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...
BMCBI
2007
179views more  BMCBI 2007»
13 years 8 months ago
Gene selection with multiple ordering criteria
Background: A microarray study may select different differentially expressed gene sets because of different selection criteria. For example, the fold-change and p-value are two co...
James J. Chen, Chen-An Tsai, ShengLi Tzeng, Chun-H...
ALIFE
2008
13 years 7 months ago
Exploring the Operational Characteristics of Inference Algorithms for Transcriptional Networks by Means of Synthetic Data
The development of structure-learning algorithms for gene regulatory networks depends heavily on the availability of synthetic data sets that contain both the original network and ...
Koenraad Van Leemput, Tim Van den Bulcke, Thomas D...
BMCBI
2010
148views more  BMCBI 2010»
13 years 8 months ago
Applying unmixing to gene expression data for tumor phylogeny inference
Background: While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall int...
Russell Schwartz, Stanley Shackney
BMCBI
2006
131views more  BMCBI 2006»
13 years 8 months ago
Hybridization interactions between probesets in short oligo microarrays lead to spurious correlations
Background: Microarrays measure the binding of nucleotide sequences to a set of sequence specific probes. This information is combined with annotation specifying the relationship ...
Michal J. Okoniewski, Crispin J. Miller