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...
Main Authors: | , , |
---|---|
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 |
id |
doaj-dc3fa63b35f548e0922ea518afe0095e |
---|---|
record_format |
Article |
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 |
_version_ |
1724628599611326464 |