ebdbNet: Empirical Bayes Dynamic Bayesian Network Inference

ebdbNet is an R package for reverse-engineering directed gene regulatory networks from time-course gene expression data using Dynamic Bayesian networks (DBN) and empirical Bayes methodology. The package offers the flexibility to incorporate hidden states (e.g., unknown transcription factors or genes not included on a particular microarray) or driving inputs (e.g., known transcription factors).

ebdbNet is written in a C script that interfaces with R. The current release is ebdbNet version 1.1. It can be downloaded from this page and from CRAN.

The changes between subsequent releases of ebdbNet are documented in the release history. Previous releases of ebdbNet may also be downloaded from this page, but these are obsolete and should only be used for reference purposes.


The ebdbNet package is maintained by Andrea Rau (email). The methods implemented in the package were jointly developed by:

  • Andrea Rau (Purdue University)
  • Florence Jaffrézic (INRA-GABI, Jouy-en-Josas, France)
  • Jean-Louis Foulley (INRA-GABI, Jouy-en-Josas, France)
  • R. W. Doerge (Departments of Statistics and Agronomy, Purdue University)


ebdbNet is distributed under the terms of the GNU General Public License, version 3 or later.