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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...
CPM
2005
Springer
109views Combinatorics» more  CPM 2005»
14 years 1 months ago
Using PQ Trees for Comparative Genomics
Permutations on strings representing gene clusters on genomes have been studied earlier in [18, 14, 3, 12, 17] and the idea of a maximal permutation pattern was introduced in [12]....
Gad M. Landau, Laxmi Parida, Oren Weimann
HIPC
2009
Springer
13 years 5 months ago
Comparing the performance of clusters, Hadoop, and Active Disks on microarray correlation computations
Abstract--Microarray-based comparative genomic hybridization (aCGH) offers an increasingly fine-grained method for detecting copy number variations in DNA. These copy number variat...
Jeffrey A. Delmerico, Nathanial A. Byrnes, Andrew ...
ISMB
2000
13 years 8 months ago
Mining for Putative Regulatory Elements in the Yeast Genome Using Gene Expression Data
We have developed a set of methods and tools for automatic discovery of putative regulatory signals in genome sequences. The analysis pipeline consists of gene expression data clu...
Jaak Vilo, Alvis Brazma, Inge Jonassen, Alan J. Ro...
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BMCBI
2004
208views more  BMCBI 2004»
13 years 7 months ago
Hybrid clustering for microarray image analysis combining intensity and shape features
Background: Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identif...
Jörg Rahnenführer, Daniel Bozinov