Results 21 to 30 of about 814,413 (282)
Abstract Complex networks, which constitute the main subject of network science, have been wide and extensively adopted for representing, characterizing, and modeling an ample range of structures and phenomena from both theoretical and applied perspectives.
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The Sznajd cellular automata corresponds to one of the simplest and yet most interesting models of complex systems. While the traditional two-dimensional Sznajd model tends to a consensus state (pro or cons), the assignment of the contrary to the dominant opinion to some of its cells during the system evolution is known to provide stabilizing feedback ...
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Deciphering the physiological response of Escherichia coli under high ATP demand
One long‐standing question in microbiology is how microbes buffer perturbations in energy metabolism. In this study, we systematically analyzed the impact of different levels of ATP demand in Escherichia coli under various conditions (aerobic and ...
Simon Boecker +6 more
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Network-based prediction of drug combinations
Combination therapy holds great promise, but discovery remains challenging. Here, the authors propose a method to identify efficacious drug combinations for specific diseases, and find that successful combinations tend to target separate neighbourhoods ...
Feixiong Cheng +2 more
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Fragmentation of outage clusters during the recovery of power distribution grids
Here the authors, by using data from three electrical companies in the USA, find that the recovery duration of an outage is connected with the downtime of its nearby outages and blackout intensity and present a cluster-based recovery framework.
Hao Wu +5 more
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Exploring complex networks [PDF]
The study of networks pervades all of science, from neurobiology to statistical physics. The most basic issues are structural: how does one characterize the wiring diagram of a food web or the Internet or the metabolic network of the bacterium Escherichia coli? Are there any unifying principles underlying their topology?
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Publisher Correction: Network-based prediction of drug combinations
The original version of this Article contained an error in Acknowledgements, which incorrectly omitted the following: ‘This work was also supported by NHLBI grant P01HL132825 to A.-L.B.’ This has been corrected in both the PDF and HTML versions of the ...
Feixiong Cheng +2 more
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Principled approach to the selection of the embedding dimension of networks
Network embedding is a machine learning technique for construction of low-dimensional representations of large networks. Gu et al. propose a method for the identification of an optimal embedding dimension for the encoding of network structural ...
Weiwei Gu +3 more
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Alcohol consumption is now common practice worldwide, and functional brain networks are beginning to reveal the complex interactions observed with alcohol consumption and abstinence.
Hope Peterson +7 more
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