MOfinder: A Novel Algorithm for Detecting Overlapping Modules from Protein-Protein Interaction Network

Qi Yu,Jing-Fei Huang,Gong-Hua Li

doi:10.1155/2012/103702

Abstract

Since organism development and many critical cell biology processes are organized in modular patterns, many algorithms have been proposed to detect modules. In this study, a new method, MOfinder, was developed to detect overlapping modules in a protein-protein interaction (PPI) network. We demonstrate that our method is more accurate than other 5 methods. Then, we applied MOfinder to yeast and human PPI network and explored the overlapping information. Using the overlapping modules of human PPI network, we constructed the module-module communication network. Functional annotation showed that the immune-related and cancer-related proteins were always together and present in the same modules, which offer some clues for immune therapy for cancer. Our study around overlapping modules suggests a new perspective on the analysis of PPI network and improves our understanding of disease.

Highlights

protein-protein interaction (PPI) networks have been widely used to understand biology at the system level [1,2,3]
Since organism development and many critical cell biology processes are organized in modular patterns, many algorithms have been proposed to detect modules
Zds1 can bind phosphatase type 2A (PP2A) to control mitotic progression [12], and it participates in Set3C complex during budding processes and repress meiotic process [13], so Zds1 may serve as a bridge between mitosis and meiosis

Summary

Introduction

PPI networks have been widely used to understand biology at the system level [1,2,3]. Zds can bind PP2A to control mitotic progression [12], and it participates in Set3C complex during budding processes and repress meiotic process [13], so Zds may serve as a bridge between mitosis and meiosis. We define these three modules as overlapping modules and define the shared protein as the overlapping nodes. The overlapping modules can form a module-module communication network. Construction of such network can be helpful for understanding the coordinated relationship between different biological processes

Methods

Results

Conclusion