Reconstruction of Network Evolutionary History from Extant Network Topology and Duplication History

TL;DR

This paper introduces a likelihood-based method to reconstruct the evolutionary history of protein-protein interaction networks using current network topology and duplication data, improving accuracy over existing methods.

Contribution

The paper presents a novel likelihood-based approach for inferring network evolution history from PPI network topology and duplication relationships, outperforming previous methods.

Findings

The approach achieves higher reconstruction accuracy than existing methods.

Estimated growth parameters align well with literature predictions.

Simulations validate the effectiveness of the proposed method.

Abstract

Genome-wide protein-protein interaction (PPI) data are readily available thanks to recent breakthroughs in biotechnology. However, PPI networks of extant organisms are only snapshots of the network evolution. How to infer the whole evolution history becomes a challenging problem in computational biology. In this paper, we present a likelihood-based approach to inferring network evolution history from the topology of PPI networks and the duplication relationship among the paralogs. Simulations show that our approach outperforms the existing ones in terms of the accuracy of reconstruction. Moreover, the growth parameters of several real PPI networks estimated by our method are more consistent with the ones predicted in literature.