Modeling Interactome: Scale-Free or Geometric?

TL;DR

This paper compares scale-free and geometric models for protein-protein interaction networks, demonstrating that geometric models more accurately fit the data than the widely used scale-free models.

Contribution

It introduces a geometric modeling approach for PPI networks and shows its superiority over traditional scale-free models in fitting real data.

Findings

Scale-free models do not fit PPI data well

Geometric models provide a better fit for PPI networks

The study challenges the dominance of scale-free assumptions in biological networks

Abstract

Networks have been used to model many real-world phenomena to better understand the phenomena and to guide experiments in order to predict their behavior. Since incorrect models lead to incorrect predictions, it is vital to have a correct model. As a result, new techniques and models for analyzing and modeling real-world networks have recently been introduced. One example of large and complex networks involves protein-protein interaction (PPI) networks. We demonstrate that the currently popular scale-free model of PPI networks fails to fit the data in several respects. We show that a random geometric model provides a much more accurate model of the PPI data.