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» Cross-Platform Analysis with Binarized Gene Expression Data
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RECOMB
2002
Springer
14 years 8 months ago
A new approach to analyzing gene expression time series data
We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved timepoints, clustering, and dataset alignment. Each expression p...
Ziv Bar-Joseph, Georg Gerber, David K. Gifford, To...
BMCBI
2008
259views more  BMCBI 2008»
13 years 8 months ago
DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcripti
Background: A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted w...
Evert-Jan Blom, Sacha A. F. T. van Hijum, Klaas J....
BMCBI
2006
131views more  BMCBI 2006»
13 years 8 months ago
SIMAGE: simulation of DNA-microarray gene expression data
Background: Simulation of DNA-microarray data serves at least three purposes: (i) optimizing the design of an intended DNA microarray experiment, (ii) comparing existing pre-proce...
Casper J. Albers, Ritsert C. Jansen, Jan Kok, Osca...
BMCBI
2010
115views more  BMCBI 2010»
13 years 8 months ago
Importance of replication in analyzing time-series gene expression data: Corticosteroid dynamics and circadian patterns in rat l
Background: Microarray technology is a powerful and widely accepted experimental technique in molecular biology that allows studying genome wide transcriptional responses. However...
Tung T. Nguyen, Richard R. Almon, Debra C. DuBois,...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 9 months ago
Discovering significant OPSM subspace clusters in massive gene expression data
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...