Sciweavers

161 search results - page 12 / 33
» Clustering gene expression patterns of fly embryos
Sort
View
BMCBI
2010
115views more  BMCBI 2010»
14 years 10 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,...
JCB
2002
160views more  JCB 2002»
14 years 10 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
RECOMB
2001
Springer
15 years 10 months ago
Context-specific Bayesian clustering for gene expression data
The recent growth in genomic data and measurements of genome-wide expression patterns allows us to apply computational tools to examine gene regulation by transcription factors. I...
Yoseph Barash, Nir Friedman
BMCBI
2007
126views more  BMCBI 2007»
14 years 10 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
BMCBI
2008
142views more  BMCBI 2008»
14 years 10 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu