Novel centrality metrics for studying essentiality in protein‐protein interaction networks based on group structures

In this work, we introduce centrality metrics based on group structures, and we show their performance in estimating importance in protein‐protein interaction networks (PPINs). The centrality metrics introduced are extensions of well‐known nodal metrics. However, instead of focusing on a single node...

Full description

Saved in:
Bibliographic Details
Published in:Networks 2022-07, Vol.80 (1), p.3-50
Main Authors: Rasti, Saeid, Vogiatzis, Chrysafis
Format: Article
Language:English
Subjects:
biological networks
centrality
Combinatorial analysis
combinatorial branch‐and‐bound
Complexity
group centrality
Integer programming
Mixed integer
network structures
Nodes
Proteins
protein‐protein interaction networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this work, we introduce centrality metrics based on group structures, and we show their performance in estimating importance in protein‐protein interaction networks (PPINs). The centrality metrics introduced are extensions of well‐known nodal metrics. However, instead of focusing on a single node, we focus on that node and the set of nodes around it. Furthermore, we require the set of nodes to induce a specific pattern or structure. The structures investigated range from the “stricter“ induced stars and cliques, to a “looser” definition of a representative structure. We derive the computational complexity of all metrics and provide mixed integer programming formulations; due to the problem complexity and the size of PPINs, using commercial solvers is not always viable. Hence, we propose a combinatorial branch‐and‐bound solution approach. We conclude by showing the effectiveness of the proposed metrics in identifying essential proteins in Helicobacter pylori and comparing them to nodal metrics.
ISSN:0028-3045
1097-0037
DOI:10.1002/net.22071