Changing internal and external conditions can influence the long-term behavior of the Boolean network model. The perturbation of a Boolean network by stripping a component of the system or simulating a surplus of another component can lead to different attractors. Obviously, the number of possible perturbations and combinations of perturbations increases with the size of the network. Manual screening a set of possible components for combinations, that have a desired effect on the long-term behavior, can be time consuming. We developed a method to automatically screen for perturbations that lead to a user-specified change in the networks behavior.
Simulation of the network under perturbation conditions allows to get a deeper understanding of the dynamics in the Boolean network model.
Getting Started :
The downloaded jar file is runnable and can be started by double-clicking. To run the application a java version (JRE) 8.71 or later is required (https://java.com/download/).
For automatic screening for perturbations switch to the exhaustive simulation panel via the simulation menubar. On the right side the attractors of the network are displayed. The button "Perturbation Screening" starts the automatic screening routine. This routine is sperated into three major steps :
Finally, the perturbation sets which show the previously selected effects on the long-term behavior of the network are shown.
By double-clicking a perturbation set of interest the resulting attractors are displayed.
The "Save"-Button stores a log-file with the settings of the perturbation screening and its results.
Our paper "Inflammatory response of mesenchymal stromal cells after in vivo exposure with selected trauma-related factors and polytrauma serum" has been published in PLoS One.
Our paper "3D Network exploration and visualisation for lifespan data" has been published in BMC Bioinformatics.