This work appears to complement an existingproject, ”Bio-inpired reverse engineering of regula-tory networks”[STH09], proposes a new algorithminspired in the artificial development technique per-forming reverse engineering over regulatory networks.The present project studies that article addressingpossible weaknesses and scalability issues. Neverthe-less, during the investigation some updates have beenperformed over the algorithm, improving the previ-ous results in some scenarios. Moreover DARBNshave been used as representation, looking for an alter-native update schema and its possible improvementsover results. Lastly, software reusable tools have beenimplemented and documented to allow additional ex-periments.5