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» Clustering Genes Using Heterogeneous Data Sources
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ALMOB
2006
135views more  ALMOB 2006»
13 years 11 months ago
P-value based visualization of codon usage data
Two important and not yet solved problems in bacterial genome research are the identification of horizontally transferred genes and the prediction of gene expression levels. Both ...
Peter Meinicke, Thomas Brodag, Wolfgang Florian Fr...
BMCBI
2008
143views more  BMCBI 2008»
13 years 11 months ago
Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering
Background: The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, ...
Shibu Yooseph, Weizhong Li, Granger G. Sutton
BMCBI
2004
181views more  BMCBI 2004»
13 years 10 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
BMCBI
2007
126views more  BMCBI 2007»
13 years 11 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...
BIBE
2003
IEEE
128views Bioinformatics» more  BIBE 2003»
14 years 4 months ago
A Repulsive Clustering Algorithm for Gene Expression Data
: - Facing the development of microarray technology, clustering is currently a leading technique to gene expression data analysis. In this paper, we propose a novel algorithm calle...
Chyun-Shin Cheng, Shiuan-Sz Wang