ArticleNature communications2013
Realistic control of network dynamics.
Article in Nature communications, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
99 citing papers in PubMed.
- Community structure-regulation coupling reveals optimal information diffusion.Nature communications · 2026Article
- A complex network perspective on brain disease.Biological reviews of the Cambridge Philosophical Society · 2026Review
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- Determining interaction directionality in complex biochemical networks from stationary measurements.Scientific reports · 2025Article
- Control of cascading failures using protective measures.Scientific reports · 2024Article
- Cell reprogramming design by transfer learning of functional transcriptional networks.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Article
- Control of complex systems with generalized embedding and empirical dynamic modeling.PloS one · 2024Article
- A Strategy Utilizing Protein-Protein Interaction Hubs for the Treatment of Cancer Diseases.International journal of molecular sciences · 2023Review
- Identifying important nodes in complex networks based on extended degree and E-shell hierarchy decomposition.Scientific reports · 2023Article
- Resonant learning in scale-free networks.PLoS computational biology · 2023Article
- The expanding horizons of network neuroscience: From description to prediction and control.NeuroImage · 2022Review
- Prevalence and scalable control of localized networks.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- NETISCE: a network-based tool for cell fate reprogramming.NPJ systems biology and applications · 2022Article
- AI Pontryagin or how artificial neural networks learn to control dynamical systems.Nature communications · 2022Article
- Functional observability and target state estimation in large-scale networks.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Network Control Models With Personalized Genomics Data for Understanding Tumor Heterogeneity in Cancer.Frontiers in oncology · 2022Review
- Informational architecture across non-living and living collectives.Theory in biosciences = Theorie in den Biowissenschaften · 2021Review
- Perspectives of Girls and Young Women Affected by Commercial Sexual Exploitation: mHealth as a Tool to Increase Engagement in Care.Journal of health care for the poor and underserved · 2021Article
- Heuristic assessment of choices for risk network control.Scientific reports · 2021Article
39 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The control of complex networks is of paramount importance in areas as diverse as ecosystem management, emergency response and cell reprogramming. A fundamental property of networks is that perturbations to one node can affect other nodes, potentially causing the entire system to change behaviour or fail. Here we show that it is possible to exploit the same principle to control network behaviour. Our approach accounts for the nonlinear dynamics inherent to real systems, and allows bringing the system to a desired target state even when this state is not directly accessible due to constraints that limit the allowed interventions. Applications show that this framework permits reprogramming a network to a desired task, as well as rescuing networks from the brink of failure-which we illustrate through the mitigation of cascading failures in a power-grid network and the identification of potential drug targets in a signalling network of human cancer.
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What OpenQuestion holds
Registered trials
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.