Abstract Modular Response Analysis (MRA) is an effective method to infer biological networks from perturbation data. However, it has several limitations, such as strong sensitivity to noise, need of performing independent perturbations that hit a single node at a time, and linear approximation of dependencies within the network. Previously, we addressed MRA sensitivity to noise by revisiting MRA as a multilinear regression problem. Here, we provide new contributions to complement this theory.
