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Modeling Nonlinear Gene Regulatory Networks from Time Series Gene Expression Data., , , , , and . J. Bioinform. Comput. Biol., 6 (5): 961-979 (2008)Comparing Pearson, Spearman and Hoeffding's d Measure for Gene Expression Association Analysis., , , , , and . J. Bioinform. Comput. Biol., 7 (4): 663-684 (2009)Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates., , , , , , and . BMC Syst. Biol., (2008)GEDI: a user-friendly toolbox for analysis of large-scale gene expression data., , , and . BMC Bioinform., (2007)Modeling gene expression regulatory networks with the sparse vector autoregressive model., , , , , , and . BMC Syst. Biol., (2007)Identification of Granger Causality between Gene Sets., , , , , , and . J. Bioinform. Comput. Biol., 8 (4): 679-701 (2010)Evaluating different methods of microarray data normalization., , , , and . BMC Bioinform., (2006)Inferring Contagion in Regulatory Networks., , , , , , , and . IEEE ACM Trans. Comput. Biol. Bioinform., 8 (2): 570-576 (2011)Time-varying modeling of gene expression regulatory networks using the wavelet dynamic vector autoregressive method., , , , , and . Bioinform., 23 (13): 1623-1630 (2007)