Defining transcription modules using large-scale gene expression data

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FABIA: factor analysis for bicluster acquisition (2010, background): “Received on December 23, 2009; revised on March 26, 2010; accepted on April 20, 2010”
Advantages and limitations of current network inference methods (2010, background): “Genes belonging to the same module act in concert under certain environmental cue”
Geometric Interpretation of Gene Coexpression Network Analysis (2008, background): “Common global properties include modular organization [1,2], the presence of highly connected hub nodes, and approximate ‘scale free topology’ [3,4].”
QUBIC: a qualitative biclustering algorithm for analyses of gene expression data (2009, methodology): “The application results on these data sets indicate that our program outperforms the existing and popular biclustering tools, such as SAMBA (14), ISA (20), BIMAX (13), RMSBE (22) and a hierarchical clustering method (HCL) in both the identification accuracy and the computational efficiency.”
Toward a Comprehensive Atlas of the Physical Interactome of Saccharomyces cerevisiae*S (2007, background): “Finally, it is known that genes encoding physically interacting proteins are more likely to have similar expression profiles (10, 23, 27, 28), and so we examined the distribution of Pearson correlation coefficients between expression patterns of interacting pairs over a set of 1000 previously publis”