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» Gene set analysis for longitudinal gene expression data
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BMCBI
2007
198views more  BMCBI 2007»
13 years 7 months ago
Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation
Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measu...
Nicola Neretti, Daniel Remondini, Marc Tatar, John...
IJKDB
2010
141views more  IJKDB 2010»
13 years 4 months ago
Mining Frequent Boolean Expressions: Application to Gene Expression and Regulatory Modeling
Regulatory network analysis and other bioinformatics tasks require the ability to induce and represent arbitrary boolean expressions from data sources. We introduce a novel framew...
Mohammed Javeed Zaki, Naren Ramakrishnan, Lizhuang...
BMCBI
2008
126views more  BMCBI 2008»
13 years 7 months ago
Relating gene expression data on two-component systems to functional annotations in Escherichia coli
Background: Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionall...
Anne M. Denton, Jianfei Wu, Megan K. Townsend, Pre...
BMCBI
2011
12 years 11 months ago
A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
Background: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) ...
Alfredo A. Kalaitzis, Neil D. Lawrence
SP
2008
IEEE
134views Security Privacy» more  SP 2008»
13 years 7 months ago
Discover gene specific local co-regulations from time-course gene expression data
Discovering gene co-regulatory relationships is one of most important research in DNA microarray data analysis. The problem of gene specific co-regulation discovery is to, for a p...
Ji Zhang, Qigang Gao, Hai H. Wang