Efficient computation of minimal perturbation sets in gene regulatory networks.

摘要: In the last few decades, technological and experimental advancements have enabled a more precise understanding of mode action drugs with respect to human cell signaling pathways positively influenced design new drug compounds. However, as compounds has become increasingly target-specific, overall effects on adjacent cellular remain difficult predict because complexity interactions involved. Off-target are known influence their efficacy safety. Similarly, which target-specific also suffer from lack scope might be too limited in context signaling. Even situations where targeted by known, presence point mutations some components can render therapy ineffective considerable target subpopulation. Some these issues addressed predicting Minimal Intervention Sets (MIS) elements that when perturbed give rise pre-defined phenotype. These minimal gene perturbation sets then further used screen library order discover effective therapies. This manuscript describes algorithms regulatory network lead defined Algorithms implemented our Boolean modeling toolbox, GenYsis. The software binaries GenYsis available for download http://www.vital-it.ch/software/genYsis/.