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A review on computational systems biology of pathogen–host interactions

Pathogens manipulate the cellular mechanisms of host organisms via pathogen–host interactions (PHIs) in order to take advantage of the capabilities of host cells, leading to infections. The crucial role of these interspecies molecular interactions in initiating and sustaining infections necessitates...

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Autores principales: Durmuş, Saliha, Çakır, Tunahan, Özgür, Arzucan, Guthke, Reinhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4391036/
https://www.ncbi.nlm.nih.gov/pubmed/25914674
http://dx.doi.org/10.3389/fmicb.2015.00235
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author Durmuş, Saliha
Çakır, Tunahan
Özgür, Arzucan
Guthke, Reinhard
author_facet Durmuş, Saliha
Çakır, Tunahan
Özgür, Arzucan
Guthke, Reinhard
author_sort Durmuş, Saliha
collection PubMed
description Pathogens manipulate the cellular mechanisms of host organisms via pathogen–host interactions (PHIs) in order to take advantage of the capabilities of host cells, leading to infections. The crucial role of these interspecies molecular interactions in initiating and sustaining infections necessitates a thorough understanding of the corresponding mechanisms. Unlike the traditional approach of considering the host or pathogen separately, a systems-level approach, considering the PHI system as a whole is indispensable to elucidate the mechanisms of infection. Following the technological advances in the post-genomic era, PHI data have been produced in large-scale within the last decade. Systems biology-based methods for the inference and analysis of PHI regulatory, metabolic, and protein–protein networks to shed light on infection mechanisms are gaining increasing demand thanks to the availability of omics data. The knowledge derived from the PHIs may largely contribute to the identification of new and more efficient therapeutics to prevent or cure infections. There are recent efforts for the detailed documentation of these experimentally verified PHI data through Web-based databases. Despite these advances in data archiving, there are still large amounts of PHI data in the biomedical literature yet to be discovered, and novel text mining methods are in development to unearth such hidden data. Here, we review a collection of recent studies on computational systems biology of PHIs with a special focus on the methods for the inference and analysis of PHI networks, covering also the Web-based databases and text-mining efforts to unravel the data hidden in the literature.
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spelling pubmed-43910362015-04-24 A review on computational systems biology of pathogen–host interactions Durmuş, Saliha Çakır, Tunahan Özgür, Arzucan Guthke, Reinhard Front Microbiol Microbiology Pathogens manipulate the cellular mechanisms of host organisms via pathogen–host interactions (PHIs) in order to take advantage of the capabilities of host cells, leading to infections. The crucial role of these interspecies molecular interactions in initiating and sustaining infections necessitates a thorough understanding of the corresponding mechanisms. Unlike the traditional approach of considering the host or pathogen separately, a systems-level approach, considering the PHI system as a whole is indispensable to elucidate the mechanisms of infection. Following the technological advances in the post-genomic era, PHI data have been produced in large-scale within the last decade. Systems biology-based methods for the inference and analysis of PHI regulatory, metabolic, and protein–protein networks to shed light on infection mechanisms are gaining increasing demand thanks to the availability of omics data. The knowledge derived from the PHIs may largely contribute to the identification of new and more efficient therapeutics to prevent or cure infections. There are recent efforts for the detailed documentation of these experimentally verified PHI data through Web-based databases. Despite these advances in data archiving, there are still large amounts of PHI data in the biomedical literature yet to be discovered, and novel text mining methods are in development to unearth such hidden data. Here, we review a collection of recent studies on computational systems biology of PHIs with a special focus on the methods for the inference and analysis of PHI networks, covering also the Web-based databases and text-mining efforts to unravel the data hidden in the literature. Frontiers Media S.A. 2015-04-09 /pmc/articles/PMC4391036/ /pubmed/25914674 http://dx.doi.org/10.3389/fmicb.2015.00235 Text en Copyright © 2015 Durmuş, Çakır, Özgür and Guthke. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Durmuş, Saliha
Çakır, Tunahan
Özgür, Arzucan
Guthke, Reinhard
A review on computational systems biology of pathogen–host interactions
title A review on computational systems biology of pathogen–host interactions
title_full A review on computational systems biology of pathogen–host interactions
title_fullStr A review on computational systems biology of pathogen–host interactions
title_full_unstemmed A review on computational systems biology of pathogen–host interactions
title_short A review on computational systems biology of pathogen–host interactions
title_sort review on computational systems biology of pathogen–host interactions
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4391036/
https://www.ncbi.nlm.nih.gov/pubmed/25914674
http://dx.doi.org/10.3389/fmicb.2015.00235
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