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» Clustering cancer gene expression data: a comparative study
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BMCBI
2008
107views more  BMCBI 2008»
15 years 6 months ago
A mixture model approach to sample size estimation in two-sample comparative microarray experiments
Background: Choosing the appropriate sample size is an important step in the design of a microarray experiment, and recently methods have been proposed that estimate sample sizes ...
Tommy S. Jørstad, Herman Midelfart, Atle M....
CPM
2005
Springer
109views Combinatorics» more  CPM 2005»
15 years 11 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
BMCBI
2007
97views more  BMCBI 2007»
15 years 6 months ago
SIRAC: Supervised Identification of Regions of Aberration in aCGH datasets
Background: Array comparative genome hybridization (aCGH) provides information about genomic aberrations. Alterations in the DNA copy number may cause the cell to malfunction, lea...
Carmen Lai, Hugo M. Horlings, Marc J. van de Vijve...
BMCBI
2007
127views more  BMCBI 2007»
15 years 6 months ago
Characterization of protein-interaction networks in tumors
Background: Analyzing differential-gene-expression data in the context of protein-interaction networks (PINs) yields information on the functional cellular status. PINs can be for...
Alexander Platzer, Paul Perco, Arno Lukas, Bernd M...
BMCBI
2004
169views more  BMCBI 2004»
15 years 6 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...