The regression network software developed for this project can produce networks with or without cycles (referred to as regression networks and Bayesian networks respectively in the paper). To make the inference computationally tractable for genome-wide applications, the algorithm allows a maximum of two incoming edges per gene. The algorithm uses a model averaging approach to improve performance.
Download the regression networks code from the PLoS 2007 Network Inference Paper