Reconstructing static and dynamic models of signaling pathways using Modular Response Analysis. Issue 9 (June 2018)

• Record Type: Journal Article
• Authors: Santra, Tapesh; Rukhlenko, Oleksii; Zhernovkov, Vadim; Kholodenko, Boris N.
• Is Part Of: Current opinion in systems biology. Issue 9(2018)
• Page Start: 11
• Page End: 21
• Publication Date: 2018-06
• Subjects: Systems biology -- Periodicals; 570
• DOI: 10.1016/j.coisb.2018.02.003
• Languages: English
• ISSNs: 2452-3100

Abstract

Abstract: In this review we discuss the origination and evolution of Modular Response Analysis (MRA), which is a physics-based method for reconstructing quantitative topological models of biochemical pathways. We first focus on the core theory of MRA, demonstrating how both the direction and the strength of local, causal connections between network modules can be precisely inferred from the global responses of the entire network to a sufficient number of perturbations, under certain conditions. Subsequently, we analyze statistical reformulations of MRA and show how MRA is used to build and calibrate mechanistic models of biological networks. We further discuss what sets MRA apart from other network reconstruction methods and outline future directions for MRA-based methods of network reconstruction. Highlights: Evolution of Modular Response Analysis (MRA) related methods is reviewed. MRA reconstructs connections and their strength from global perturbation responses. Statistical reformulations of MRA can handle incomplete data and biological noise. Use of prior information by Bayesian MRA greatly improves reconstruction accuracy. ODE models can be developed and calibrated using MRA-reconstructed networks.