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Complex diseases can be modeled as damage to intracellular networks thatresults in abnormal cell behaviors. Network-based dynamic models such asBoolean models have been employed to model a variety of biological systemsincluding those corresponding to disease. Previous work designed compensatoryinteractions to stabilize an attractor of a Boolean network after single nodedamage. We generalize this method to a multinode damage scenario and to thesimultaneous stabilization of multiple steady state attractors. We classify theemergent situations, with a special focus on combinatorial effects, andcharacterize each class through simulation. We explore how the structural andfunctional properties of the network affect its resilience and its possiblerepair scenarios. We demonstrate the method's applicability to twointracellular network models relevant to cancer. This work has implications indesigning prevention strategies for complex disease.

Compensatory interactions to stabilize multiple steady states or mitigate the effects of multiple deregulations in biological networks