Controllability in cancer metabolic networks according to drug targets as driver nodes.

Networks are employed to represent many nonlinear complex systems in the real world. The topological aspects and relationships between the structure and function of biological networks have been widely studied in the past few decades. However dynamic and control features of complex networks have not...

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Autores principales:	Yazdan Asgari, Ali Salehzadeh-Yazdi, Falk Schreiber, Ali Masoudi-Nejad
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9b950a9558af453180bd89c706227136
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id	oai:doaj.org-article:9b950a9558af453180bd89c706227136
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spelling	oai:doaj.org-article:9b950a9558af453180bd89c7062271362021-11-18T08:44:56ZControllability in cancer metabolic networks according to drug targets as driver nodes.1932-620310.1371/journal.pone.0079397https://doaj.org/article/9b950a9558af453180bd89c7062271362013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24282504/?tool=EBIhttps://doaj.org/toc/1932-6203Networks are employed to represent many nonlinear complex systems in the real world. The topological aspects and relationships between the structure and function of biological networks have been widely studied in the past few decades. However dynamic and control features of complex networks have not been widely researched, in comparison to topological network features. In this study, we explore the relationship between network controllability, topological parameters, and network medicine (metabolic drug targets). Considering the assumption that targets of approved anticancer metabolic drugs are driver nodes (which control cancer metabolic networks), we have applied topological analysis to genome-scale metabolic models of 15 normal and corresponding cancer cell types. The results show that besides primary network parameters, more complex network metrics such as motifs and clusters may also be appropriate for controlling the systems providing the controllability relationship between topological parameters and drug targets. Consequently, this study reveals the possibilities of following a set of driver nodes in network clusters instead of considering them individually according to their centralities. This outcome suggests considering distributed control systems instead of nodal control for cancer metabolic networks, leading to a new strategy in the field of network medicine.Yazdan AsgariAli Salehzadeh-YazdiFalk SchreiberAli Masoudi-NejadPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 11, p e79397 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yazdan Asgari Ali Salehzadeh-Yazdi Falk Schreiber Ali Masoudi-Nejad Controllability in cancer metabolic networks according to drug targets as driver nodes.
description	Networks are employed to represent many nonlinear complex systems in the real world. The topological aspects and relationships between the structure and function of biological networks have been widely studied in the past few decades. However dynamic and control features of complex networks have not been widely researched, in comparison to topological network features. In this study, we explore the relationship between network controllability, topological parameters, and network medicine (metabolic drug targets). Considering the assumption that targets of approved anticancer metabolic drugs are driver nodes (which control cancer metabolic networks), we have applied topological analysis to genome-scale metabolic models of 15 normal and corresponding cancer cell types. The results show that besides primary network parameters, more complex network metrics such as motifs and clusters may also be appropriate for controlling the systems providing the controllability relationship between topological parameters and drug targets. Consequently, this study reveals the possibilities of following a set of driver nodes in network clusters instead of considering them individually according to their centralities. This outcome suggests considering distributed control systems instead of nodal control for cancer metabolic networks, leading to a new strategy in the field of network medicine.
format	article
author	Yazdan Asgari Ali Salehzadeh-Yazdi Falk Schreiber Ali Masoudi-Nejad
author_facet	Yazdan Asgari Ali Salehzadeh-Yazdi Falk Schreiber Ali Masoudi-Nejad
author_sort	Yazdan Asgari
title	Controllability in cancer metabolic networks according to drug targets as driver nodes.
title_short	Controllability in cancer metabolic networks according to drug targets as driver nodes.
title_full	Controllability in cancer metabolic networks according to drug targets as driver nodes.
title_fullStr	Controllability in cancer metabolic networks according to drug targets as driver nodes.
title_full_unstemmed	Controllability in cancer metabolic networks according to drug targets as driver nodes.
title_sort	controllability in cancer metabolic networks according to drug targets as driver nodes.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/9b950a9558af453180bd89c706227136
work_keys_str_mv	AT yazdanasgari controllabilityincancermetabolicnetworksaccordingtodrugtargetsasdrivernodes AT alisalehzadehyazdi controllabilityincancermetabolicnetworksaccordingtodrugtargetsasdrivernodes AT falkschreiber controllabilityincancermetabolicnetworksaccordingtodrugtargetsasdrivernodes AT alimasoudinejad controllabilityincancermetabolicnetworksaccordingtodrugtargetsasdrivernodes
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Controllability in cancer metabolic networks according to drug targets as driver nodes.

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