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Despite the large quantity of information available, thorough researches invarious biological databases are still needed in order to reconstruct andunderstand the steps that lead to known or new phenomena. By usingprotein-protein interaction networks and algorithms to extract relevantinterconnections among proteins of interest, it is possible to assemblesubnetworks from global interactomes. Using these extracted networks it ispossible to use algorithms to predict signal directions while activation andinhibition effects can be predicted using RNA interference screenings. Theresult of this approach is the automatic generation of boolean networks. Thisway of modelling dynamical systems allows the discovery of steady states andthe prediction of stimuli response.

Assembling biological boolean networks using manually curated databases and prediction algorithms