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Fine-Scale Dissection of Functional Protein Network Organization by Statistical Network Analysis

Revealing organizational principles of biological networks is an important goal of systems biology. In this study, we sought to analyze the dynamic organizational principles within the protein interaction network by studying the characteristics of individual neighborhoods of proteins within the netw...

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Detalles Bibliográficos
Autores principales: Komurov, Kakajan, Gunes, Mehmet H., White, Michael A.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2699632/
https://www.ncbi.nlm.nih.gov/pubmed/19554104
http://dx.doi.org/10.1371/journal.pone.0006017
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author Komurov, Kakajan
Gunes, Mehmet H.
White, Michael A.
author_facet Komurov, Kakajan
Gunes, Mehmet H.
White, Michael A.
author_sort Komurov, Kakajan
collection PubMed
description Revealing organizational principles of biological networks is an important goal of systems biology. In this study, we sought to analyze the dynamic organizational principles within the protein interaction network by studying the characteristics of individual neighborhoods of proteins within the network based on their gene expression as well as protein-protein interaction patterns. By clustering proteins into distinct groups based on their neighborhood gene expression characteristics, we identify several significant trends in the dynamic organization of the protein interaction network. We show that proteins with distinct neighborhood gene expression characteristics are positioned in specific localities in the protein interaction network thereby playing specific roles in the dynamic network connectivity. Remarkably, our analysis reveals a neighborhood characteristic that corresponds to the most centrally located group of proteins within the network. Further, we show that the connectivity pattern displayed by this group is consistent with the notion of “rich club connectivity” in complex networks. Importantly, our findings are largely reproducible in networks constructed using independent and different datasets.
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spelling pubmed-26996322009-06-24 Fine-Scale Dissection of Functional Protein Network Organization by Statistical Network Analysis Komurov, Kakajan Gunes, Mehmet H. White, Michael A. PLoS One Research Article Revealing organizational principles of biological networks is an important goal of systems biology. In this study, we sought to analyze the dynamic organizational principles within the protein interaction network by studying the characteristics of individual neighborhoods of proteins within the network based on their gene expression as well as protein-protein interaction patterns. By clustering proteins into distinct groups based on their neighborhood gene expression characteristics, we identify several significant trends in the dynamic organization of the protein interaction network. We show that proteins with distinct neighborhood gene expression characteristics are positioned in specific localities in the protein interaction network thereby playing specific roles in the dynamic network connectivity. Remarkably, our analysis reveals a neighborhood characteristic that corresponds to the most centrally located group of proteins within the network. Further, we show that the connectivity pattern displayed by this group is consistent with the notion of “rich club connectivity” in complex networks. Importantly, our findings are largely reproducible in networks constructed using independent and different datasets. Public Library of Science 2009-06-24 /pmc/articles/PMC2699632/ /pubmed/19554104 http://dx.doi.org/10.1371/journal.pone.0006017 Text en This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
spellingShingle Research Article
Komurov, Kakajan
Gunes, Mehmet H.
White, Michael A.
Fine-Scale Dissection of Functional Protein Network Organization by Statistical Network Analysis
title Fine-Scale Dissection of Functional Protein Network Organization by Statistical Network Analysis
title_full Fine-Scale Dissection of Functional Protein Network Organization by Statistical Network Analysis
title_fullStr Fine-Scale Dissection of Functional Protein Network Organization by Statistical Network Analysis
title_full_unstemmed Fine-Scale Dissection of Functional Protein Network Organization by Statistical Network Analysis
title_short Fine-Scale Dissection of Functional Protein Network Organization by Statistical Network Analysis
title_sort fine-scale dissection of functional protein network organization by statistical network analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2699632/
https://www.ncbi.nlm.nih.gov/pubmed/19554104
http://dx.doi.org/10.1371/journal.pone.0006017
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