Control of multilayer biological networks and applied to target identification of complex diseases

Abstract Background Networks have been widely used to model the structures of various biological systems. The ultimate aim of research on biological networks is to steer biological system structures to desired states by manipulating signals. Despite great advances in the linear control of single-lay...

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Main Authors: Wei Zheng, Dingjie Wang, Xiufen Zou
Format: Article
Language:English
Published: BMC 2019-05-01
Series:BMC Bioinformatics
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12859-019-2841-2
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spelling doaj-dc3fa63b35f548e0922ea518afe0095e2020-11-25T03:18:09ZengBMCBMC Bioinformatics1471-21052019-05-0120111210.1186/s12859-019-2841-2Control of multilayer biological networks and applied to target identification of complex diseasesWei Zheng0Dingjie Wang1Xiufen Zou2School of Mathematics and Statistics, Wuhan UniversitySchool of Mathematics and Statistics, Wuhan UniversitySchool of Mathematics and Statistics, Wuhan UniversityAbstract Background Networks have been widely used to model the structures of various biological systems. The ultimate aim of research on biological networks is to steer biological system structures to desired states by manipulating signals. Despite great advances in the linear control of single-layer networks, it has been observed that many complex biological systems have a multilayer networked structure and extremely complicated nonlinear processes. Result In this study, we propose a general framework for controlling nonlinear dynamical systems with multilayer networked structures by formulating the problem as a minimum union optimization problem. In particular, we offer a novel approach for identifying the minimal driver nodes that can steer a multilayered nonlinear dynamical system toward any desired dynamical attractor. Three disease-related biology multilayer networks are used to demonstrate the effectiveness of our approaches. Moreover, in the set of minimum driver nodes identified by the algorithm we proposed, we confirmed that some nodes can act as drug targets in the biological experiments. Other nodes have not been reported as drug targets; however, they are also involved in important biological processes from existing literature. Conclusions The proposed method could be a promising tool for determining higher drug target enrichment or more meaningful steering nodes for studying complex diseases.http://link.springer.com/article/10.1186/s12859-019-2841-2Multilayer networksNetwork controlNonlinear dynamical systemsIISG algorithmDriver nodes
collection DOAJ
language English
format Article
sources DOAJ
author Wei Zheng
Dingjie Wang
Xiufen Zou
spellingShingle Wei Zheng
Dingjie Wang
Xiufen Zou
Control of multilayer biological networks and applied to target identification of complex diseases
BMC Bioinformatics
Multilayer networks
Network control
Nonlinear dynamical systems
IISG algorithm
Driver nodes
author_facet Wei Zheng
Dingjie Wang
Xiufen Zou
author_sort Wei Zheng
title Control of multilayer biological networks and applied to target identification of complex diseases
title_short Control of multilayer biological networks and applied to target identification of complex diseases
title_full Control of multilayer biological networks and applied to target identification of complex diseases
title_fullStr Control of multilayer biological networks and applied to target identification of complex diseases
title_full_unstemmed Control of multilayer biological networks and applied to target identification of complex diseases
title_sort control of multilayer biological networks and applied to target identification of complex diseases
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2019-05-01
description Abstract Background Networks have been widely used to model the structures of various biological systems. The ultimate aim of research on biological networks is to steer biological system structures to desired states by manipulating signals. Despite great advances in the linear control of single-layer networks, it has been observed that many complex biological systems have a multilayer networked structure and extremely complicated nonlinear processes. Result In this study, we propose a general framework for controlling nonlinear dynamical systems with multilayer networked structures by formulating the problem as a minimum union optimization problem. In particular, we offer a novel approach for identifying the minimal driver nodes that can steer a multilayered nonlinear dynamical system toward any desired dynamical attractor. Three disease-related biology multilayer networks are used to demonstrate the effectiveness of our approaches. Moreover, in the set of minimum driver nodes identified by the algorithm we proposed, we confirmed that some nodes can act as drug targets in the biological experiments. Other nodes have not been reported as drug targets; however, they are also involved in important biological processes from existing literature. Conclusions The proposed method could be a promising tool for determining higher drug target enrichment or more meaningful steering nodes for studying complex diseases.
topic Multilayer networks
Network control
Nonlinear dynamical systems
IISG algorithm
Driver nodes
url http://link.springer.com/article/10.1186/s12859-019-2841-2
work_keys_str_mv AT weizheng controlofmultilayerbiologicalnetworksandappliedtotargetidentificationofcomplexdiseases
AT dingjiewang controlofmultilayerbiologicalnetworksandappliedtotargetidentificationofcomplexdiseases
AT xiufenzou controlofmultilayerbiologicalnetworksandappliedtotargetidentificationofcomplexdiseases
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