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

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 demonstra...

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Detalles Bibliográficos
Autores principales: Yu, Qi, Li, Gong-Hua, Huang, Jing-Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303734/
https://www.ncbi.nlm.nih.gov/pubmed/22500072
http://dx.doi.org/10.1155/2012/103702
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author Yu, Qi
Li, Gong-Hua
Huang, Jing-Fei
author_facet Yu, Qi
Li, Gong-Hua
Huang, Jing-Fei
author_sort Yu, Qi
collection PubMed
description 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.
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spelling pubmed-33037342012-04-12 MOfinder: A Novel Algorithm for Detecting Overlapping Modules from Protein-Protein Interaction Network Yu, Qi Li, Gong-Hua Huang, Jing-Fei J Biomed Biotechnol Research Article 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. Hindawi Publishing Corporation 2012 2012-02-08 /pmc/articles/PMC3303734/ /pubmed/22500072 http://dx.doi.org/10.1155/2012/103702 Text en Copyright © 2012 Qi Yu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yu, Qi
Li, Gong-Hua
Huang, Jing-Fei
MOfinder: A Novel Algorithm for Detecting Overlapping Modules from Protein-Protein Interaction Network
title MOfinder: A Novel Algorithm for Detecting Overlapping Modules from Protein-Protein Interaction Network
title_full MOfinder: A Novel Algorithm for Detecting Overlapping Modules from Protein-Protein Interaction Network
title_fullStr MOfinder: A Novel Algorithm for Detecting Overlapping Modules from Protein-Protein Interaction Network
title_full_unstemmed MOfinder: A Novel Algorithm for Detecting Overlapping Modules from Protein-Protein Interaction Network
title_short MOfinder: A Novel Algorithm for Detecting Overlapping Modules from Protein-Protein Interaction Network
title_sort mofinder: a novel algorithm for detecting overlapping modules from protein-protein interaction network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303734/
https://www.ncbi.nlm.nih.gov/pubmed/22500072
http://dx.doi.org/10.1155/2012/103702
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