AbstractMotivationGene networks are complex sets of regulators and interactions that govern cellular processes. Their perturbations can disrupt regular biological functions, translating into a change in cell behaviour and ability to respond to internal and external cues. Computational models of these networks can boost translation of our scientific knowledge into medical applications by predicting how cells will behave in health and disease, or respond to stimuli such as a drug treatment. The development of such models requires effective ways to read, manipulate and analyse the increasing amount of existing, and newly deposited gene network data.ResultsWe developed BioSWITCH, a command-line program using the BioPAX standardised language to “switch on” static regulatory networks so that they can be executed in GINML to predict cellular behaviour. Using a previously published haematopoiesis gene network, we show that BioSWITCH successfully and faithfully automates the network de-coding and re-coding into an executable logical network. BioSWITCH also supports the integration of a BioPAX model into an existing GINML graph.AvailabilitySource code available at https://github.com/CBigOxf/[email protected]; [email protected]
Assigning function to natural allelic variation via dynamic modeling of gene network induction