Dynamic probabilistic threshold networks to infer signaling pathways from time-course perturbation data

Network inference deals with the reconstruction of molecular networks from experimental data. Given N molecular species, the challenge is to find the underlying network. Due to data limitations, this typically is an illposed problem, and requires the integration of prior biological knowledge or strong regularization.