ArticleNature communications2016
A geometrical approach to control and controllability of nonlinear dynamical networks.
Article in Nature communications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Convergent information flows explain recurring firing patterns in cerebral cortex.Nature neuroscience · 2026Article
- Inferring gene regulatory networks using transcriptional profiles as dynamical attractors.PLoS computational biology · 2023Article
- Thalamic bursts modulate cortical synchrony locally to switch between states of global functional connectivity in a cognitive task.PLoS computational biology · 2022Article
- Discovering adaptation-capable biological network structures using control-theoretic approaches.PLoS computational biology · 2022Article
- Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease.Nature communications · 2021Article
- Bow-tie architecture of gene regulatory networks in species of varying complexity.Journal of the Royal Society, Interface · 2021Article
- [State regulation for complex biological networks based on dynamic optimization algorithms].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2020Article
- Reconciling periodic rhythms of large-scale biological networks by optimal control.Royal Society open science · 2020Article
- A topology-dynamics-based control strategy for multi-dimensional complex networked dynamical systems.Scientific reports · 2019Article
- A novel network control model for identifying personalized driver genes in cancer.PLoS computational biology · 2019Article
- Harnessing tipping points in complex ecological networks.Journal of the Royal Society, Interface · 2019Article
- Irrelevance of linear controllability to nonlinear dynamical networks.Nature communications · 2019Article
- Controlling large Boolean networks with single-step perturbations.Bioinformatics (Oxford, England) · 2019Article
- Disease classification via gene network integrating modules and pathways.Royal Society open science · 2019Article
- Control of multilayer biological networks and applied to target identification of complex diseases.BMC bioinformatics · 2019Article
- Next Generation Networks: Featuring the Potential Role of Emerging Applications in Translational Oncology.Journal of clinical medicine · 2019Article
- Impulsive control of a nonlinear dynamical network and its application to biological networks.Journal of biological physics · 2019Article
- Prediction of Optimal Drug Schedules for Controlling Autophagy.Scientific reports · 2019Article
- Optimal regulation of blood glucose level in Type I diabetes using insulin and glucagon.PloS one · 2019Article
- Clarifying cognitive control and the controllable connectome.Wiley interdisciplinary reviews. Cognitive science · 2019Review
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Authors and funding
7 authors.
Funding
Abstract
In spite of the recent interest and advances in linear controllability of complex networks, controlling nonlinear network dynamics remains an outstanding problem. Here we develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another, assuming that the former is undesired and the latter is desired. To make our framework practically meaningful, we consider restricted parameter perturbation by imposing two constraints: it must be experimentally realizable and applied only temporarily. We introduce the concept of attractor network, which allows us to formulate a quantifiable controllability framework for nonlinear dynamical networks: a network is more controllable if the attractor network is more strongly connected. We test our control framework using examples from various models of experimental gene regulatory networks and demonstrate the beneficial role of noise in facilitating control.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.