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Trade-offs between driving nodes and time-to-control in complex networks.

ABSTRACT: Recent advances in control theory provide us with efficient tools to determine the minimum number of driving (or driven) nodes to steer a complex network towards a desired state. Furthermore, we often need to do it within a given time window, so it is of practical importance to understand the trade-offs between the minimum number of driving/driven nodes and the minimum time required to reach a desired state. Therefore, we introduce the notion of actuation spectrum to capture such trade-offs, which we used to find that in many complex networks only a small fraction of driving (or driven) nodes is required to steer the network to a desired state within a relatively small time window. Furthermore, our empirical studies reveal that, even though synthetic network models are designed to present structural properties similar to those observed in real networks, their actuation spectra can be dramatically different. Thus, it supports the need to develop new synthetic network models able to replicate controllability properties of real-world networks.

SUBMITTER: Pequito S

PROVIDER: S-EPMC5215470 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Trade-offs between driving nodes and time-to-control in complex networks.

Pequito Sérgio S Preciado Victor M VM Barabási Albert-László AL Pappas George J GJ

Scientific reports 20170105

Recent advances in control theory provide us with efficient tools to determine the minimum number of driving (or driven) nodes to steer a complex network towards a desired state. Furthermore, we often need to do it within a given time window, so it is of practical importance to understand the trade-offs between the minimum number of driving/driven nodes and the minimum time required to reach a desired state. Therefore, we introduce the notion of actuation spectrum to capture such trade-offs, whi ...[more]

PMID: 28054597

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Project description:Trade-offs between competitive ability and resistance to top-down control manifest the "kill-the-winner" hypothesis that explains how mortality caused by protists and viruses can promote bacterial diversity. However, the existence of such trade-offs has rarely been investigated in natural marine bacterial communities. To address this question, we conducted on-board dilution experiments to manipulate top-down control pressure (protists only or protists plus viruses [protists+viruses] combined) and then applied 16S rRNA gene high-throughput sequencing techniques to assess the responses of each bacterial taxon. Dilution experiments enabled us to measure the top-down-control-free growth rate as the competitive ability and top-down-control-caused mortality as the reverse of resistance to top-down control. Overall, bacterial taxa with higher top-down-control-free growth rates were accompanied by lower top-down-control-caused resistance. Furthermore, competition-resistance trade-offs were stronger and more consistent when top-down control was caused by protists+viruses combined than by protists only. When protists+viruses were diluted, the bacterial rank abundance distribution became steepened and evenness and richness were decreased. However, when protists were diluted, only richness decreased. Our results indicate the existence of competition-resistance trade-offs in marine microbes and demonstrate the positive impacts of such trade-offs on bacterial diversity. Regardless, the strength of the competition-resistance trade-offs and the impacts on bacterial diversity were contingent on whether top-down control was caused by protists+viruses combined or protists only. IMPORTANCE We addressed the "kill-the-winner" hypothesis from the perspective of its principle (the competition-resistance trade-off) in marine bacterial communities incubated in situ. Our results supported the existence of competition-resistance trade-offs and the positive effect on bacterial community diversity. The study linked theoretical expectations and complex natural systems and provided new knowledge regarding how top-down controls and competition trade-offs shaped natural bacterial communities.

Dataset Information

Trade-offs between driving nodes and time-to-control in complex networks.

Publications

Trade-offs between driving nodes and time-to-control in complex networks.

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