Causal loop and Stock-Flow Modeling of Signal Transduction Pathways

TL;DR

This paper introduces a system dynamics approach using causal loop and stock-flow diagrams to model and analyze cell signaling pathways, demonstrating its effectiveness through a case study on ERK signaling.

Contribution

It proposes a novel three-step process for modeling signal transduction pathways using system dynamics, applied to complex cell signaling pathways with comparative analysis.

Findings

System dynamics effectively models cell signaling pathways.

The approach identifies biochemical reaction paths and loops.

Simulations show ease and effectiveness compared to other methods.

Abstract

System dynamics is a popular approach in many fields of science and technology, but it has not been investigated for cell signaling pathways yet. It is a well formulated methodology used to analyze the components of a system considering the cause-effect relationships. The two main components of system dynamics modeling, Causal Loop and Stocks-Flow diagrams, make possible to model the dynamics of the system with the ability to analyze it both qualitatively and quantitatively. In this paper, after introducing the system dynamics modeling approach, and giving a simple example from its usage for Michaelis Menton reactions, a three-step process is proposed for signal transduction modeling. Then in a complete example, it is applied to a case study in cell signaling pathways, namely the RKIP Influence on the ERK signaling pathway and the results is compared with an integrative modeling approach based on Petri net and ODEs. Computational simulations show the success of the system dynamic in easier and effective modeling of the cell signaling pathways, in addition to its diverse options for understanding and testing the pathway quantitatively and quantitatively at the same time in relation to other methods. More intestinally, the suggested approach here helps one to identify all biochemical reaction paths and loops for complex cell signaling pathways. It will be a good step forward to define dominant systems for such complex cell signaling pathways.