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BMCBI
2008
160views more  BMCBI 2008»
13 years 7 months ago
A comparison of four clustering methods for brain expression microarray data
Background: DNA microarrays, which determine the expression levels of tens of thousands of genes from a sample, are an important research tool. However, the volume of data they pr...
Alexander L. Richards, Peter Holmans, Michael C. O...
BIBE
2004
IEEE
107views Bioinformatics» more  BIBE 2004»
13 years 11 months ago
Enhanced pClustering and Its Applications to Gene Expression Data
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
Sungroh Yoon, Christine Nardini, Luca Benini, Giov...
RECOMB
2000
Springer
13 years 11 months ago
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
Nir Friedman, Michal Linial, Iftach Nachman, Dana ...
BMCBI
2006
164views more  BMCBI 2006»
13 years 7 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta
BMCBI
2010
104views more  BMCBI 2010»
13 years 7 months ago
Response network analysis of differential gene expression in human epithelial lung cells during avian influenza infections
Background: The recent emergence of the H5N1 influenza virus from avian reservoirs has raised concern about future influenza strains of high virulence emerging that could easily i...
Ken Tatebe, Ahmet Zeytun, Ruy M. Ribeiro, Robert H...