Reverse control of biological networks to restore phenotype landscapes

Biological systems consist of genetic elements and their regulatory interactions, forming networks that maintain life. However, accumulated alterations such as DNA damage can distort biological behavior, leading to undesirable responses to stimulus. This raises the question of whether we can restore their nominal stimulus-response relationships. Current control approaches tend to enforce a single desired response rather than restore the proper capacity for variable responses to different stimulus. Here, we present an algebraic reverse control (ARC) framework for reversion of altered biological networks. ARC leverages matrix operations to quantify the phenotype landscape of the altered network and identifies reverse control targets for recovering the phenotype landscape of a nominal network. ARC is scalable to large Boolean networks and identifies effective control targets to restore biological behavior.