Dominating scale-free networks with variable scaling exponent: heterogeneous networks are not difficult to control
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This work addresses complex network controllability from the perspective of the minimum dominating set (MDS) and shows that the more heterogeneous a network degree distribution is, the easier it is to control the entire system.Abstract:
The possibility of controlling and directing a complex system's behavior at will is rooted in its interconnectivity and can lead to significant advances in disparate fields, ranging from nationwide energy saving to therapies that involve multiple targets. In this work, we address complex network controllability from the perspective of the minimum dominating set (MDS). Our theoretical calculations, simulations using artificially generated networks as well as real-world network analyses show that the more heterogeneous a network degree distribution is, the easier it is to control the entire system. We demonstrate that relatively few nodes are needed to control the entire network if the power-law degree exponent is smaller than 2, whereas many nodes are required if it is larger than 2.read more
Citations
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Control Principles of Complex Networks
TL;DR: Recent advances on the controllability and the control of complex networks are reviewed, exploring the intricate interplay between a system's structure, captured by its network topology, and the dynamical laws that govern the interactions between the components.
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Data based identification and prediction of nonlinear and complex dynamical systems
TL;DR: The recent advances in this forefront and rapidly evolving field of reconstructing nonlinear and complex dynamical systems from measured data or time series are reviewed, aiming to cover topics such as compressive sensing, noised-induced dynamical mapping, perturbations, reverse engineering, synchronization, inner composition alignment, global silencing and Granger Causality.
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Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets
Arunachalam Vinayagam,Travis E. Gibson,Ho-Joon Lee,Bahar Yilmazel,Charles Roesel,Charles Roesel,Yanhui Hu,Young Guen Kwon,Amitabh Sharma,Yang-Yu Liu,Yang-Yu Liu,Yang-Yu Liu,Norbert Perrimon,Albert-László Barabási +13 more
TL;DR: It is found that 21% of the proteins in the PPI network are indispensable, Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network’s control property is critical for the transition between healthy and disease states.
Journal ArticleDOI
Controllability in protein interaction networks
TL;DR: Minimum dominating sets of proteins (MDSets) were determined, proteins that play a role in the control of the underlying interaction webs in human and yeast protein interaction networks and were found that MDSet proteins were enriched with essential, cancer-related, and virus-targeted genes.
Journal ArticleDOI
Data Based Identification and Prediction of Nonlinear and Complex Dynamical Systems
TL;DR: The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics.
References
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