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This content will become publicly available on July 21, 2026

Title: GRPhIN: Graphlet Characterization of Regulatory and Physical Interaction Networks
Graphs are powerful tools for modeling and analyzing molecular interaction networks. Graphs typically represent either undirected physical interactions or directed regulatory relationships, which can obscure a particular protein’s functional context. Graphlets can describe local topologies and patterns within graphs, and combining physical and regulatory interactions offer new graphlet configurations that can provide biological insights. We present GRPhIN, a tool for characterizing graphlets and protein roles within graphlets in mixed physical and regulatory interaction networks. We describe the graphlets of mixed networks in B. subtilis, C. elegans, D. melanogaster, D. rerio, and S. cerevisiae and examine local topologies of proteins and subnetworks related to the oxidative stress response pathway. We found a number of graphlets that were abundant in all species, specific node positions (orbits) within graphlets that were over-represented in stress-associated proteins, and rarely-occurring graphlets that were over-represented in oxidative stress subnetworks. These results showcase the potential for using graphlets in mixed physical and regulatory interaction networks to identify new patterns beyond a single interaction type.  more » « less
Award ID(s):
1750981
PAR ID:
10621900
Author(s) / Creator(s):
; ;
Editor(s):
Shao, Mingfu
Publisher / Repository:
Oxford Academic
Date Published:
Journal Name:
Bioinformatics Advances
ISSN:
2635-0041
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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