Testing and overcoming the limitations of modular response analysis.

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 the sensitivity of MRA to noise by reinterpreting MRA as a multilinear regression problem. We demonstrated the advantages of this approach over the conventional MRA and other known inference methods, particularly in handling noise measurements and nonlinear networks. Here, we provide new contributions to complement this theory. First, we overcome the need of perturbations to be independent, thereby augmenting MRA applicability. Second, using analysis

SUBMITTER: Borg JP 

PROVIDER: S-EPMC11891662 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature