Analyzing effective models: An example from JAK/STAT5 signaling

TL;DR

This paper demonstrates how analyzing assumptions in effective models, exemplified by a delay equation for JAK/STAT5 signaling, can prevent misinterpretations and deepen understanding of biological systems.

Contribution

It provides a method to analyze and validate effective models by examining underlying assumptions, illustrated through a case study on JAK/STAT5 signaling.

Findings

Clarified assumptions behind the delay equation model

Showed how assumption analysis prevents incorrect conclusions

Validated model assumptions with experimental data

Abstract

In systems biology effective models are widely used due to the complexity of biological system. They result from a coarse-graining process which employs specific assumptions. Frequently one does not start with a model taking all details into account and then performs a coarse-graining process, but rather one starts right away with the effective equations and often the underlying assumptions remain hidden or unclear. We exemplify the analysis of an effective model by analyzing a time delay equation for the JAK/STAT5 signaling pathway and show how one can avoid wrong conclusions and obtain a deeper understanding of the biological system . By analyzing the assumptions leading to a coarse-grained model one might be able to gain new insight into the involved biological processes. Further, the compliance of the model with experimental data can be considered as a validation of the assumptions made in the derivation of the mathematical equations.