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» The ParTriCluster Algorithm for Gene Expression Analysis
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CIBCB
2007
IEEE
13 years 8 months ago
Associative Artificial Neural Network for Discovery of Highly Correlated Gene Groups Based on Gene Ontology and Gene Expression
Abstract-- The advance of high-throughput experimental technologies poses continuous challenges to computational data analysis in functional and comparative genomics studies. Gene ...
Ji He, Xinbin Dai, Xuechun Zhao
BMCBI
2007
112views more  BMCBI 2007»
13 years 4 months ago
Inferring biological functions and associated transcriptional regulators using gene set expression coherence analysis
Background: Gene clustering has been widely used to group genes with similar expression pattern in microarray data analysis. Subsequent enrichment analysis using predefined gene s...
Tae-Min Kim, Yeun-Jun Chung, Mun-Gan Rhyu, Myeong ...
BMCBI
2006
203views more  BMCBI 2006»
13 years 4 months ago
Genome-wide prediction of transcriptional regulatory elements of human promoters using gene expression and promoter analysis dat
Background: A complete understanding of the regulatory mechanisms of gene expression is the next important issue of genomics. Many bioinformaticians have developed methods and alg...
Seon-Young Kim, YongSung Kim
BIBE
2003
IEEE
128views Bioinformatics» more  BIBE 2003»
13 years 10 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
BMCBI
2005
124views more  BMCBI 2005»
13 years 4 months ago
ErmineJ: Tool for functional analysis of gene expression data sets
Background: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories...
Homin K. Lee, William Braynen, Kiran Keshav, Paul ...