Modular response analysis reformulated as a multilinear regression problem

Abstract

MotivationModular response analysis (MRA) is a well-established method to infer biological networks from perturbation data. Classically, MRA requires the solution of a linear system and results are sensitive to noise in the data and perturbation intensities. Applications to networks of 10 nodes or more are difficult due to noise propagation. ResultsWe propose a new formulation of MRA as a multilinear regression problem. This enables to integrate all the replicates and potential, additional perturbations in a larger, over determined and more stable system of equations. More relevant confidence intervals on network parameters can be obtained and we show competitive performance for networks of size up to 100. Prior knowledge integration in the form of known null edges further improves these results. Availability and implementationThe R code used to obtain the presented results is available from GitHub: https://github.com/J-P-Borg/BioInformatics ContactPatrice.ravel@umontpellier.fr