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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2010
96views more  BMCBI 2010»
15 years 20 hour ago
A statistical framework for differential network analysis from microarray data
Background: It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of gene...
Ryan Gill, Somnath Datta, Susmita Datta
PSB
2004
15 years 1 months ago
Modeling Cellular Processes with Variational Bayesian Cooperative Vector Quantizer
Gene expression of a cell is controlled by sophisticated cellular processes. The capability of inferring the states of these cellular processes would provide insight into the mech...
Xinghua Lu, Milos Hauskrecht, Roger S. Day
BMCBI
2008
133views more  BMCBI 2008»
15 years 15 hour ago
A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data
Background: Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible f...
Luca Corradi, Marco Fato, Ivan Porro, Silvia Scagl...
IJON
2008
128views more  IJON 2008»
14 years 12 months ago
Independent arrays or independent time courses for gene expression time series data analysis
In this paper we apply three different independent component analysis (ICA) methods, including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA), to gene exp...
Sookjeong Kim, Jong Kyoung Kim, Seungjin Choi
BIOINFORMATICS
2007
195views more  BIOINFORMATICS 2007»
15 years 19 hour ago
Context-dependent clustering for dynamic cellular state modeling of microarray gene expression
Motivation: High-throughput expression profiling allows researchers to study gene activities globally. Genes with similar expression profiles are likely to encode proteins that ma...
Shinsheng Yuan, Ker-Chau Li